astroglial plasticity within the rat orofacial primary motor cortex … · 2019-11-15 · ii...
TRANSCRIPT
Astroglial Plasticity within the Rat Orofacial Primary Motor Cortex Induced by Endodontic Treatment versus Tooth
Extraction
by
Jacqueline Lopez Gross
A thesis submitted in conformity with the requirements
for the degree of Master of Science in Endodontics
Faculty of Dentistry
University of Toronto
© Copyright by Jacqueline Lopez Gross 2018
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Astroglial Plasticity within the Rat Orofacial Primary Motor Cortex
Induced by Endodontic Treatment versus Tooth Extraction
Jacqueline Lopez Gross
Master of Science in Endodontics
Faculty of Dentistry
University of Toronto
2018
Abstract
Objective: To optimise the CLARITY technique that renders brain tissue optically transparent,
immunolabelling and light-sheet microscopy for 3D-characterisation of astroglial
cytoarchitecture and morphology within the orofacial primary motor cortex of rats
receiving endodontic versus tooth extraction treatment.
Methods: Rats received either extraction, endodontic-, sham- or no-treatment of the right
maxillary molar teeth. After one week, 2 mm-thick brain sections of the orofacial primary motor
cortex were cleared and immunolabelled with astroglial markers. 3D-images were acquired with
light-sheet microscope and Imaris software was used to characterise and quantify cytoarchitecture
and morphological features of astroglial processes.
Results: As compared with endodontic-, sham- and no-treatment, tooth extraction produced
significantly thinner and straighter astroglial processes within layer-I of a laminar motor cortex.
Conclusion/significance: Tooth extraction but not endodontic treatment induces astroglial
plasticity within the rat primary motor cortex that controls orofacial motor functions. Astroglia
may be a therapeutic target for preventing/curing postoperative motor impairments.
iii
Acknowledgments
First, I would like to express my gratitude to Dr. Limor Avivi-Arber, who captivated me with her
passion for neuroscience and guided me with her expertise to accomplish every step of this
assignment. Thank you for challenging me with a very demanding project that felt like learning a
new language and required all my brain cells to work in coherence beyond expectations. Thank
you for exposing me to novel cutting-edge experiments and techniques that blew out my brain
with excitation and satisfaction. I am extremely grateful and honoured by your commitment and
patience. I could not ask for a better supervisor and role model.
I would like to thank Dr. Bettina Basrani, my Program Director, for her support and
encouragement throughout my studies. Thanks are due to the valuable inputs from Dr. Pavel
Cherkas that helped me better understand this project; I appreciate his kind editorial efforts and
wise advice as an endodontist and neuroscientist. I would also like to thank my thesis examiners
Dr. Boris Kablar and Ze’ev Seltzer whose comments have further improves the clarity of my
thesis.
The burden of the highly demanding experiments, imaging and data analysis was lessened
substantially by the support and friendship of Dr. Maryam Zanjir, Idan Yona, Ho Jung Hwang
(Amelia), Imran Alidina and Caitlin Sherry. Thank you, guys.
I am also grateful to Kristin Overton and Ailey Crow from Dr. Carl Deisseroth’s Lab at Stanford
University, California, USA; Kim Lau and Paul Paroutis from the Imaging Facility at SickKids
Hospital, Toronto, Canada; Irene Constantini from the European Laboratory for Non-linear
Spectroscopy at the University of Florence, Italy; Yosuke Niibori from Dr. Paul Frankland’s Lab,
Faculty of Pharmacy, University of Toronto; Sayed Abdullah from the Integrated Nanotechnology
and Biomedical Sciences Laboratory, University of Toronto, and to Nikolaos Ziogas from Dr.
Vassilis Koliatsos’s Laboratory, John Hopkins Medicine. Their availability and valuable
information helped us optimise the CLARITY technique and 3D imaging with the light-sheet
microscope. I would also like to thanks Bitplane Imaris support team, Daniel Miranda and
Mathew Gastinger for the hours of on-line support.
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Lastly, but most importantly, I would like to express my gratitude to my parents and my parents
in-law, my sisters and sisters in-law, my brothers and brothers in-law, and in particular my very
dear daughter, Ana, and husband, Alejandro, whose love and support have helped me accomplish
this thesis. I dedicate this thesis to my family.
This work was funded by the Faculty of Dentistry Bertha Rosenstadt Fund, Foundation for
Endodontics, Alpha Omega Foundation of Canada, Canadian Academy of Endodontics, Shimon
Friedman and Calvin Torneck Endowment Fund, and the International College of Prosthodontists.
This project also received the AAE/Dentsply Sirona Resident Award for the best Oral Research
Presentation at the 2018 American Association of Endodontics Annual Meeting, and the
International College of Prosthodontists Research Travel Award to present this work at the 2019
annual meeting in Amsterdam, The Netherlands.
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Table of Contents Acknowledgments ................................................................................................................... iii
Table of Contents ..................................................................................................................... v
List of Tables ......................................................................................................................... viii
List of Figures ......................................................................................................................... ix
List of Abbreviations ............................................................................................................. xiv
Chapter 1 .................................................................................................................................. 1
Introduction ......................................................................................................................... 1
1.1 Overview .................................................................................................................... 1
1.2 Main Somatosensory and Motor Innervation of Orofacial Tissues ........................... 3
1.2.1 Sensory Receptors ............................................................................................ 3
1.2.2 Major Somatosensory Afferent Pathways ........................................................ 4
1.2.3 The Orofacial Primary Motor Cortex: Neuronal Cytoarchitecture, Connectivity and Major Motor Efferent Pathways .......................................... 7
1.2.4 Clinical Implications ...................................................................................... 10
1.2.4.1 Consequences of Endodontic Treatment and Tooth Extraction ...... 10
1.3 Motor Cortex Neuroplasticity Induced by Altered Sensory Inputs and Motor Function ................................................................................................................... 11
1.3.1 Clinical Significance of Motor Cortex Neuroplasticity ................................. 12
1.4 Glial Cells ................................................................................................................ 14
1.4.1 Astroglial Cells: Cytoarchitecture and Morphology ...................................... 15
1.4.2 Astroglial cells: Role in Regulating Neuronal Function ................................ 16
1.4.3 Astroglial Plasticity ........................................................................................ 18
1.5 The CLARITY Technique ....................................................................................... 18
1.6 Light-Sheet Fluorescence Microscopy ..................................................................... 20
1.7 Statement of the Problem, Hypothesis and Objectives ............................................ 21
1.8 General Aim ............................................................................................................. 22
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1.9 Hypothesis ................................................................................................................ 22
1.10 Specific Aims ........................................................................................................... 23
Materials and Methods ...................................................................................................... 24
2.1 Animals .................................................................................................................... 24
2.2 Study Groups and General Study Design ................................................................. 25
2.3 Animal Experiments ................................................................................................. 26
2.3.1 Anaesthesia and Aseptic Procedures .............................................................. 26
2.3.2 Tooth Extraction, Pulpectomy and Sham Operations .................................... 26
2.3.2.1 Tooth Extraction .............................................................................. 27
2.3.2.2 Endodontic Treatment ...................................................................... 27
2.3.2.3 Sham Operation ............................................................................... 27
2.3.2.4 Postoperative Care ........................................................................... 28
2.4 The CLARITY Immunhistochemistry Technique ................................................... 29
2.4.1 Hydrogel Monomer Perfusion-Infusion ......................................................... 29
2.4.1.1 Brain Dissection ............................................................................... 31
2.4.1.2 Hydrogel Tissue Embedding ............................................................ 32
2.4.2 Hydrogel Tissue Hybridisation ...................................................................... 32
2.4.3 Passive Tissue-Clearing of Membrane Lipids ............................................... 33
2.4.3.1 Buffer Wash and Storage ................................................................. 33
2.4.4 Immunolabelling: Optimisation Protocol for Whole-Tissue .......................... 34
2.4.4.1 Whole-Tissue Immunolabelling Protocol ........................................ 34
2.4.5 Optical Clearing and Refractive Index Matching .......................................... 35
2.4.6 Whole Tissue Imaging ................................................................................... 38
2.4.6.1 Mounting Cleared Tissue for Light-Sheet Microscopy ................... 38
2.4.6.2 The Region of Interest ..................................................................... 38
2.4.6.3 Image Acquisition ............................................................................ 39
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2.4.7 Image Processing ............................................................................................ 41
2.4.7.1 Identification of Layer I ................................................................... 41
2.4.8 Quantification of Morphological Parameters of Astroglial Processes ........... 41
2.4.8.1 Morphological Parameters ............................................................... 42
2.5 Data Analysis and Sample Size Calculation ............................................................ 43
2.6 Excluded Data .......................................................................................................... 43
Results ............................................................................................................................... 46
3.1 3D Characterisation of Astroglial and Neuronal Cytoarchitecture and Morphology within the Superficial Layers of the Rat Orofacial Primary Motor Cortex .............. 46
3.2 Morphological Features of GFAP-Immunoreactive Processes: Effects of Maxillary Molar Tooth Extraction versus Endodontic Treatment ............................................ 51
Discussion .......................................................................................................................... 53
4.1 3D Visualisation of Astroglia with CLARITY ........................................................ 53
4.2 3D Characterisation of Astroglial and Neuronal Cytoarchitecture and Morphology within the Superficial Layers of the Rat Orofacial Primary Motor Cortex .............. 55
4.3 Morphological Features of GFAP-Immunoreactive Processes: Effects of Maxillary Molar Tooth Extraction versus Endodontic Treatment ............................................ 57
4.3.1 Clinical Implications ...................................................................................... 59
4.4 Study Limitations and Future Directions ................................................................. 60
Conclusions ....................................................................................................................... 63
References ......................................................................................................................... 64
viii
List of Tables
Table 1. List of Solutions, ingredients and manufacturer. ........................................................... 31
Table 2. List of conjugated antibodies used for immunolabelling. ............................................. 35
Table 3. Testing options for optical clearing and refractive index matching .............................. 37
Table 4. Summary of study groups, number of animals included or excluded from the study and
the reason for exclusion. ....................................................................................................... 45
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List of Figures
Figure 1. Illustration of main pathways showing projections of trigeminal (V) primary afferents
from the oral cavity via the trigeminal ganglion to second-order neurones in the trigeminal
brainstem sensory nuclear complex, and from there, to higher levels of the brain including the
thalamus and cerebral cortex. Vc - subnucleus caudalis, Vi – subnucleus interpolaris, Vo –
subnucleus oralis. Reprinted with permission from the Journal Critical Reviews in Oral Biology
and Medicine, Sessle B, Copyright (2000) (Sessle, 2000)………………………………………..6
Figure 2. On the right are cortical motor maps illustrating the motor representation areas of the
jaw-opening (anterior digastric) and tongue-protrusion (genioglossus) muscles within the rat left
orofacial sensorimotor cortex. The motor representations are superimposed on Nissl-stained
coronal hemisections of the left hemisphere at anteroposterior (AP) planes 2.4, 2.7, 3.0, 3.3, 3.6,
and 3.9 mm anterior to Bregma. On the left are corresponding schematic diagrams from
Swanson’s Atlas of the rat brain (Swanson, 2004) which indicate the different cortical layers in
Arabic numbers (3,4,5,6). Top right of the figure is a sagittal view diagram of the rat brain.
Reprinted with permission from John Wiley and Sons, Journal of Comparative Neurology, Brain
maps 4.0—Structure of the rat brain: An open access atlas with global nervous system
nomenclature ontology and flatmaps, Swanson L, Copyright (2018)……………………………..9
Figure 3. Image of GFAP-labelled astroglial cell within layer 5 of a mouse orofacial primary
motor cortex obtained by 3D imaging of a 40 µm – thick brain section with a spinning disk
confocal microscope (63x/1.3; water). GFAP - Glial fibrillary acidic protein, a specific marker of
astroglial cytoskeleton (Unpublished data)………………………………………..…………….16
Figure 4. Schematic representation of the ‘tripartite synapse’, neuron – astroglia – neuron.
Reprinted by permission from Springer Nature: Nature Neuroscience: Glia — more than just brain
glue, Allen N; Barres, B, Copyright (2009) (Allen and Barres, 2009)…………………………..17
Figure 5. A-C. Layout of the light-sheet Z.1 fluorescence microscope. The objective lens and
detection beam-path are perpendicular to the illumination beam-path. A laser light that is formed
into a thin sheet of light illuminates the fluorescently-labeled tissue from either one or two sides.
x
This illumination excites only fluorophores within the focal plane of the detection objective. All
fluorescent signals are collected on a camera-based detector. D-E. The light-sheet is generated
either statically by using a cylindrical lens or dynamically by high-frequency scanning of a laser
beam. Reprinted by permission from Zeiss……………………………………………………...21
Figure 6. Experiment time-line. Rats were monitored on a daily basis from the date of arrival at
the vivarium until perfusion day. Weight (yellow arrow) was measured on arrival, after
acclimation period and on the day of perfusion. Treatment (endodontic treatment, tooth extraction
or sham operation) were carried out following a 1-week acclimation (green band). Analgesics and
anti-inflammatory drugs were administered up to three days postoperatively (pink band).
Perfusion was performed on day 7 after treatment (blue band)………………………………….26
Figure 7. A. Mouth opening. B. Maxillary molar teeth. C. Extraction sockets of right maxillary
molar teeth. D. Access cavities for dental pulp extirpation of right maxillary molar teeth. E.
Radiographic image of the right maxillae showing maxillary molar teeth after pulpectomy and
restoration of access cavity with a temporary filling material. F. Radiographic image of the right
maxillae showing extraction sockets…………………………………………………………….28
Figure 8. Overview of the CLARITY technique. Step 1- Hydrogel monomer perfusion-infusion:
An optically transparent porous matrix composed of formaldehyde (red), acrylamide and
bisacrylamide (hydrogel) monomers (blue), and thermally-triggered initiators, perfusion-infused
into the brain tissue at 4 oC. The formaldehyde forms crosslinks with the tissue, and covalent links
(electron sharing) between the hydrogel monomers and tissue-proteins, nucleic acids and other
biomolecules. Step 2- Hydrogel tissue embedding: At 37 oC, the tissue-bound monomers
polymerise and create a hydrogel mesh–tissue hybrid that provides physical support to tissue
structure. Step 3- Passive clearing of membrane lipids: Passive clearing removes lipids and
molecules that remained unbound to the hydrogel. While detergent (sodium dodecyl sulfate, SDS)
micelles diffuse passively through the tissue, they capture and clear out lipid of the tissue. The
hydrogel–tissue hybrid keeps biomolecules and fine cytoarchitectural features of the brain intact,
including neuronal and glial proteins. Despite clearing, some light-scattering remains due to
heterogeneous distribution of proteins and nucleic acid complexes in the hybrid. Step 4: Standard
immunolabelling of cells or molecules. Step 5- Optical clearing and refractive index matching:
Immersion in 2,2'-thiodiethanol (TDE) solution for: optical clearing; tissue shrinkage to
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compensate for clearing-induced tissue expansion; refractive index homogenization. Step 6-
Image acquisition: Light-sheet microscopy to visualise cells in intact thick tissue. Adapted by
permission from Springer Nature: Nature Methods. CLARITY for mapping the nervous system,
Chung, K; Deisseroth, K, Copyright (2013) (Chung and Deisseroth, 2013)......…………………30
Figure 9. A. A whole brain after hybridisation. Dotted lines mark the region of 2 mm-thick
coronal section containing the orofacial primary motor cortex. B. Rostral view of a 2 mm-thick
coronal section. C. Rostral view of a 2 mm-thick coronal section after 7 days of passive clearing.
D. Rostral view of a 2 mm-thick coronal section following ~15 days of clearing; the tissue appears
clear and ‘see-through’. Notice the significant increase in the size due to swelling that occurred
during the passive clearing………………………………………………………………….…...33
Figure 10. Refractometer. Prior to the light-sheet imaging, a refractometer was used to ensure
that the Refractive Index (RI) of the 63% TDE immersion solution matches the refractive index
of the light-sheet imaging objective (i.e., 1.45)………………………………………………….37
Figure 11. The region of interest (small yellow square) selected for scanning with the light-sheet
20X CLARITY objective spanned from the cortical surface at ~4 mm lateral to midline (red line)
and included a total area of 438.9 μm x 438.9 μm x 1 mm………………………………………39
Figure 12. A. A glass capillary is attached to the caudal aspect of the 2 mm-thick brain section.
Red arrow is pointing at the area were the ROI is located. B. The glass capillary with the brain
section are attached to the Zeiss light-sheet Z1 microscope and positioned in front of the camera
(red arrow). C. Outside view of the Zeiss light-sheet Z1 microscope…………………………..40
Figure 13. A. 3D image of 1 mm-thick cortical tissue showing the features used to select the
region of interest within layer I: the pia mater, composed of NeuN+ flat-shape nuclei (red), the
glia limitans identified as a continuous layer of high intensity GFAP+ astroglial cells, cortical
layer I is characterised by a rich network of GFAP+ processes while layers II/III below show a
significantly larger number of NeuN+ nuclei and sparse GFAP+ cells. B. Illustrates the region of
interest within layer I selected for subsequent morphometric analysis of GFAP+ processes.
Bottom yellow line marks the approximate border between layer I and layers II/III. Top yellow
line marks an approximate border between layer I and the glial limitans. C. Bitplane Imaris
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software masked the GFAP+ processes (white) within the region of interest for subsequent
morphometric analysis…………………………………………………………………………..42
Figure 14. A. 3D image of 1 mm-thick brain tissue from a rat that underwent inadequate perfusion
and subsequent immunolabelling with GFAP marker in green. White arrows show >6 µm-thick
GFAP+ structures consistent with blood-filled blood vessels (scale 100 μm). B. Enlarged insert
from figure A. C and D. 3D image of 1 mm-thick brain tissue which underwent immunolabelling
with GFAP marker in green. Image shows bright and dark stripe artifacts which are a common
occurrence in light-sheet microscopy (scale 100 μm). C. A lateral view. D. A superior view……44
Figure 15. A. A 2D image of a Nissl-stained coronal section through the orofacial sensory-motor
cortex of a Sprague Dawley rat at ~ 3 mm anterior to Bregma. Superimposed are the jaw (red)
and tongue (blue) motor representation areas as we have previously mapped and documented. B.
A schematic diagram obtained from Swanson’s Atlas of the Rat Brain). Reprinted with permission
from John Wiley and Sons, Journal of Comparative Neurology, Brain maps 4.0—Structure of the
rat brain: An open access atlas with global nervous system nomenclature ontology and flatmaps,
Swanson L, Copyright (2004) (Swanson, 2004), which corresponds to the histological section in
A, indicating the different cortical layers numbered with Roman numerals from superficial to deep
(I-VI). C. A 3D image of a 438.9 µm x 438.9 µm x 1 mm (scale 50 μm) brain tissue showing the
superficial cortical layers I and II/III as well as the pia mater and glia limitans. White arrow
pointing at the pia mater, composed of NeuN+ flat-shape nuclei (red). Juxtaposing below the pia
is the glia limitans (white arrow), which comprises a continuous layer of high intensity GFAP+
astroglial cell bodies and processes. (GFAP+: immunoreactive glial fibrillary acidic protein;
NeuN+: neuronal nuclei)……………………………………………………………………..…47
Figure 16. A. Superior view of glia limitans superficialis showing high-intensity GFAP+ cells
(green; soma and processes). Superior view of a blood vessel (white arrow) penetrating the cortex;
and NeuN+ neuronal nuclei (red). (scale 50 μm) B. Lateral view of a blood vessel (white arrow)
penetrating the cortical parenchyma surrounded by GFAP+ astroglial cells (green) forming the
glia limitans perivascularis; NeuN+ neuronal nuclei are marked in red (scale 50 μm). C. Schematic
representation of the superficial membranes of the cortex showing that the glia limitans (green)
lies between the pia mater and the cerebral cortex. D. 40 µm thick image showing GFAP + cells
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(green) within the superficial layer of motor cortex forming glia limitans, DAPI (blue) labelling
of any nucleus within the cortex and the pia mater above the glia limitans (scale 50 μm).……..48
Figure 17. A. GFAP+ cells covering the cortical surface area form the glia limitans superficialis
and GFAP+ cells surrounding blood vessels form the glia perivascularis. B. Enlarged insert from
Figure A showing the glia limitans perivascularis (scale 50 μm)……………………………….49
Figure 18. A. A 3D image of a 1 mm-thick cortical tissue showing cells immunolabelled with
GFAP (GFAP+, green), a specific marker of astroglial cytoskeleton, NeuN (NeuN+, red), a
specific marker of neuronal nuclei, and DAPI (blue), a non-specific marker of cell nuclei. B. Same
image as in A showing GFAP+ cells. C. Same image as in A showing NeuN+ cells (scale 100
μm)………………………………………………………………………………………………50
Figure 19. Mean diameter (A) and straightness (B) of astroglial processes. Diameter data is
presented as group-means and SEM; Straightness data is presented as group-medians and SEM.
Tooth extraction was associated with a significantly smaller diameter and straighter astroglial
processes………………………………………………………………………………………...51
Figure 20. A. Percent volume of all GFAP-labelled cells. B. Ratio of surface area to volume of
all GFAP-labelled cells. C. Total length of all GFAP-labelled processes. Data presented as group-
means and SEM………………………………………………………………………………….52
xiv
List of Abbreviations
3D Three dimension
AP anteroposterior
ANOVA Analysis of variance
CLARITY Clear Lipid-exchanged Acrylamide-hybridized Rigid Imaging-compatible Tissue-
hYdrogel
CNS Central nervous system
DAPI 4′,6-diamidino-2-phenylindole
DNA Deoxyribonucleic acid
E.G. Ex grata
ETC electrophoresis for tissue clearing
GABA Gamma-aminobutyric acid
GB Gigabyte
GFAP Glial fibrillary acidic protein
GC-genu of corpus callosum
GG Genioglossus
GHz Gigahertz
Glt1 Glutamate transporter
HP Hewllet packard
I.E., Id est
I.M. Intramuscular
NA Numerical aperture
NaOCL Sodium hypochlorite
NeuN Neuronal nuclei marker
PBS Phosphate buffered saline
PBST Phosphate suffered saline- triton
PBT Phosphate borate triton
Post-op Post-operative
RAM Random access memory
RI Refractive index
ROI Region of interest
RPM Rounds per minute
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SDS Sodium dodecyl sulfate
TDE 2,2'-thiodiethanol
VII Facial nerve
IX Glossopharyngeal nerve
X Vagus nerve
1
Chapter 1
Introduction
1.1 Overview Many patients who undergo tooth extraction and endodontic treatments suffer from acute
orofacial sensory (e.g., pain) and/or motor (e.g., jaw movement, biting, chewing) impairments.
Clinicians often fail to adequately manage these impairments and prevent the development of
chronic conditions (e.g., phantom sensation or pain) because the underlying mechanisms are still
poorly understood (Klineberg et al., 2014; Kumar et al., 2018; Nixdorf et al., 2010b; Nixdorf et
al., 2010c; Renton, 2011). While the underlying mechanisms are poorly understood, they may
involve the orofacial primary motor cortex, the main brain region involved in the generation and
modulation of orofacial motor functions. It is important to emphasise that somatosensory inputs
from the orofacial region (e.g., oral mucosa, teeth) provide somatosensory feedback and
feedforward information that is crucial for modulating the orofacial movements. Since these
movements rely on sensory inputs, they are referred to as sensory-motor movements. Current
literature has shown in rodents that changes in sensory inputs to the motor cortex, or altered motor
functions, can induce functional neuroplastic changes in the orofacial primary motor cortex. For
example, noxious stimulation of the orofacial tissues (including tooth pulp) as well as other
intraoral manipulations such as orthodontic treatment, tooth trimming or extraction, and dental
implant surgery can all induces changes in neuronal activity and circuitry (Adachi et al., 2007;
Avivi-Arber et al., 2010b, 2015a,b; Awamleh et al., 2015; Pun et al., 2016; Sood et al., 2015; Yao
and Sessle, 2018; for review see Avivi-Arber et al., 2011d; Avivi-Arber and Sessle, 2018; Sessle
et al., 2013b). Such neuroplastic changes may contribute to the restoration of sensory-motor
functions (i.e., adaptive neuroplasticity), but may also contribute to the development and
maintenance of impaired sensory-motor behaviours including chronic pain (i.e., maladaptive
neuroplasticity). It has also been reported that the neuroplastic changes may involve and depend
on the functional integrity of non-neuronal astroglial cells since application of an astroglial
inhibitor to the surface of the orofacial primary motor cortex can reverse the neuroplasticity
induced by the noxious stimulation of the dental pulp (Awamleh et al., 2015). However, it is
unclear what the exact cortical site of action of the astroglial inhibitor was in the cited study.
2
Nevertheless, it likely diffused into the cortex to exert its effects at least on astroglial cells within
the superficial cortical layers. Indeed, Laskawi et al. showed that peripheral nerve injury induces
astroglial plasticity within layers I/II of the primary motor cortex (Laskawi et al., 1997). Peripheral
injuries (e.g., noxious stimulation of the dental pulp, orofacial nerve injury or inflammation) can
also result in structural and functional astroglial plasticity within other cortical and subcortical
regions characterised by progressive changes in the number, morphology, function, and gene
expression of astroglia within trigeminal subnucleus caudalis, thalamus and primary
somatosensory cortex (for review see Chiang et al., 2012). In fact, it has been shown that
functional astroglial plasticity is tightly coupled to structural astroglial plasticity (Liddelow and
Barres, 2015). However, no study has addressed whether endodontic treatment (i.e., dental pulp
extirpation) and tooth extraction induce structural plasticity in astroglial cells within the orofacial
primary motor cortex. Better understanding of the role and involvement of astroglia in orofacial
sensory-motor functions after dental manipulation is of clinical significance since it can assist in
the development of improved therapeutic approaches, such as targeting astroglia within the
orofacial primary motor cortex, to prevent or cure orofacial sensory-motor impairment (Hamby
and Sofroniew, 2010; Kimelberg and Nedergaard, 2010; Liddelow and Barres, 2015, 2017).
Conventional immunohistochemistry has long been a fundamental technique in neuroscience
research to explore morphological features of neuronal and non-neuronal cells in consecutive thin
(µm) brain sections. Major advancements in recent years have led to the development of the novel
CLARITY technique (i.e., Clear Lipid-exchanged Acrylamide-hybridized Rigid Imaging-
compatible Tissue-hYdrogel) that renders the brain optically transparent, and along with
immunolabelling and subsequent novel 3D imaging and automated detection of brain cells, allows
quantification of morphological features of cells within thick (mm) brain sections or even at the
whole-brain level (Chung and Deisseroth, 2013; Chung et al., 2013; Zheng and Rinaman, 2016).
However, no study has utilised the novel CLARITY technique to investigate morphological
features of astroglial processes within the superficial layer of the orofacial primary motor cortex
and their plasticity following intraoral injury.
Thus, the general aim of the present thesis was to use an animal model and the novel CLARITY
technique for 3D characterisation of astroglial cytoarchitecture and quantification of
3
morphological changes in astroglial cells within thick brain sections of the orofacial primary
motor cortex of rats receiving tooth extraction or endodontic treatment.
1.2 Main Somatosensory and Motor Innervation of Orofacial Tissues
1.2.1 Sensory Receptors Sensory receptors are specialised nerve endings in peripheral tissues that are activated by external
stimuli such as mechanical [touch, pressure, vibration and proprioceptive (i.e., muscle tension and
length)], chemical, thermal (cold, warm) or nociceptive stimuli. Receptor activation generates
action potentials that propagate through the primary afferent nerve fibre to the brainstem (or spinal
cord) and higher brain centres to generate sensations and also to modulate motor functions (see
below). Teeth and orofacial tissues, in general, are characterised by a high density of receptors
that contribute to the high sensitivity of these tissues (Byers, 1984; Fried, 2014; Sessle, 2006;
Sessle, 2011a).
The dental pulp has a rich innervation density of free nerve endings sensitive to mechanical,
thermal, chemical and noxious stimuli (Byers, 1984; Fried K., 2014; Haggard and de Boer, 2014;
Miles et al., 2004; Roth and Calmes, 1981; Sessle, 2006; Sessle, 2011a). The periodontal
ligaments that attach the tooth roots to the surrounding alveolar bone are rich in nociceptors and
specialised mechanoreceptors distributed along the roots of the teeth. The mechanoreceptors also
function as proprioceptors providing information about the amount, speed and direction of
occlusal forces (Haggard and de Boer, 2014; Linden, 1990; Miles et al., 2004; Roth and Calmes,
1981; Sessle, 2006; Sessle, 2011a). Skin and mucosa have free nerve endings and specialised
mechanoreceptors that also function as proprioceptors that are activated in response to
deformations of underlying muscles during muscle contractions and jaw movements (Haggard
and de Boer, 2014; Miles et al., 2004; Roth and Calmes, 1981; Sessle, 2006; Sessle, 2011a).
Muscle spindle and golgi tendon, as well as joints, have specialised receptors that function as
proprioceptors. Proprioceptors of skin, mucosa, muscle and joints provide information about joint
angle, muscle length, muscle tension and jaw position in space. However, it is important to note
that many orofacial muscles, including jaw-opening and facial expression muscles, have very few
4
or no muscle spindles and golgi tendon organs (Haggard and de Boer, 2014; Lazarov, 2007; Miles
et al., 2004; Roth and Calmes, 1981; Sessle, 2006; Sessle, 2011a).
1.2.2 Major Somatosensory Afferent Pathways The trigeminal nerve is the main cranial nerve carrying somatosensory and proprioceptive primary
afferent neurones projecting from orofacial receptors to the central nervous system. It has three
sensory branches: the ophthalmic branch (superior) that provides sensory innervation to most of
the scalp, forehead, and front of the head; the maxillary branch (middle) provides sensory
innervation to the cheeks, nostrils, upper lip and maxillary bone, soft tissues and teeth; and the
mandibular branch (inferior) provides sensory innervation to the anterior two thirds of the tongue,
lower lip, and mandibular bone, soft tissues, and teeth. In addition, the mandibular division also
carries efferent motor fibres to the jaw muscles of mastication (see below). Other cranial nerves
are involved in the innervation of other orofacial tissues. For example, the glossopharyngeal (IX)
and the vagus (X) nerves innervate the posterior tongue, larynx, pharynx and ears; and the facial
nerve (VII) innervates the tongue (taste), ears and periauricular skin (Haggard and de Boer, 2014;
Miles et al., 2004; Roth and Calmes, 1981; Sessle, 2006; Sessle, 2011b).
Most of the somatosensory and all the proprioceptive primary afferent nerve fibres innervating
the orofacial area project in a somatotopic manner along the trigeminal nerve branches to
terminate mainly in the ipsilateral trigeminal brainstem sensory nuclear complex which consists
of the trigeminal main sensory nucleus as well as the trigeminal spinal tract nucleus that is further
subdivided into subnuclei oralis, interpolaris and caudalis (Fig. 1). Touch, pressure, and vibration
inputs from soft tissues (e.g., tongue, skin, mucosa) and periodontal ligaments as well as dental
pulp, and some proprioceptive inputs from periodontal ligaments are conveyed to the central
nervous system via large-diameter, low threshold and fast-conducting Aβ primary afferent nerve
fibres. Nociceptive and thermoceptive inputs from the soft tissues as well as the periodontal
ligament and dental pulp are conveyed via small-diameter, high threshold and slow-conducting
Aδ and C primary afferent nerve fibres. Proprioceptive inputs from jaw muscles and other
orofacial muscles are conveyed via Aα primary afferent nerve fibres (Haggard and de Boer, 2014;
Miles et al., 2004; Roth and Calmes, 1981; Sessle, 2006; Sessle, 2011b).
5
The cell bodies of the somatosensory primary afferent nerve fibres are located in sensory ganglia
associated with the cranial nerves VII, IX and X. Generally, primary afferents can diverge and
converge to terminate in multiple subnuclei of the trigeminal brainstem sensory nuclear complex.
Primary afferent nerve fibres conveying touch inputs have their cell bodies located in the
trigeminal ganglion and they synapse mainly on second-order neurones within the principal
sensory nucleus and subnucleus oralis. The majority of these fibres ascend to the thalamus
bilaterally in a somatotopic manner via the dorsal trigeminothalamic tract (i.e., dorsal trigeminal
lemniscus). Primary afferent nerve fibres conveying nociceptive and temperature inputs also have
their cell bodies in the trigeminal ganglion, but they synapse mainly on second-order neurones
within the subnucleus caudalis as well as subnucleus interpolaris. The majority of these fibres
cross to the opposite side and ascend to the thalamus via the ventral trigeminothalamic tract (i.e.,
anterior trigeminal lemniscus) ( Haggard and de Boer, 2014; Miles et al., 2004; Roth and Calmes,
1981; Sessle, 2006; Sessle, 2011a).
Proprioceptive inputs from masticatory muscles as well as the periodontal ligament have their cell
bodies either in the trigeminal ganglion or in the mesencephalic nucleus. Proprioceptive primary
afferents with cell bodies in the trigeminal ganglion synapse on second-order neurones within the
principal sensory nucleus and subnucleus oralis. The majority of the proprioceptive primary
afferents with cell bodies in the mesencephalic nucleus synapse on alpha motor neurones within
the trigeminal motor nucleus. Alpha motor neurones project to and activate masticatory muscle
and thus proprioceptive inputs from the orofacial region can directly and reflexively impact
orofacial motor responses (for reviews, see Avivi-Arber and Sessle, 2018; Haggard and de Boer,
2014; Miles et al., 2004; Paxinos, 2004; Roth and Calmes, 1981; Sessle, 2000).
Thalamic neurones project in a somatotopic manner from the main thalamic sensory nuclei to the
primary somatosensory cortex where conscious somatosensory perception is processed.
Consequently, inputs from the different body parts are organised within the primary
somatosensory cortex in a somatotopic manner known as the somatosensory representation map
or somatosensory homunculus. Body parts that are next to each other in the periphery are also
represented next to each other in the primary somatosensory cortex and the larger the innervation
density of a body part the larger the representation. Thus, the orofacial tissues, including teeth and
jaw muscles have large representations within in the primary somatosensory cortex.
6
A large amount of sensory inputs also projects to the primary motor cortex either through the
primary somatosensory cortex or directly from thalamic sensory and motor nuclei. Somatosensory
and proprioceptive inputs from the oral region, including the teeth, provide feedback and
feedforward information necessary for modulating muscle activity and muscle forces (see below)
(for detailed review see Avivi-Arber, 2009, 2011b, 2018; Haggard and de Boer, 2014; Miles et
al., 2004; Paxinos, 2004; Sessle, 2000; Sessle et al., 2013b)
Figure 1. Illustration of main pathways showing projections of trigeminal (V) primary afferents from the oral cavity via the trigeminal ganglion to second-order neurones in the trigeminal brainstem sensory nuclear complex, and from there, to higher levels of the brain including the thalamus and cerebral cortex. Vc - subnucleus caudalis, Vi – subnucleus interpolaris, Vo – subnucleus oralis. Reprinted with permission from the Journal Critical Reviews in Oral Biology and Medicine, Sessle B, Copyright (2000) (Sessle, 2000).
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1.2.3 The Orofacial Primary Motor Cortex: Neuronal Cytoarchitecture, Connectivity and Major Motor Efferent Pathways
The primary motor cortex is the main brain region involved in the initiation and modulation of
muscle contraction and body movements. Within the primary motor cortex , the orofacial primary
motor area is involved in the initiation and modulation of muscle contraction in the orofacial
region that can give rise to bilaterally coordinated orofacial movements including elemental
movements such as jaw-opening, jaw-closing, tongue-protrusion and tongue-retrusion, as well as
semi-automatic rhythmic movements such as mastication and swallowing (for reviews, see Avivi-
Arber et al., 2011d, 2018; Sessle et al., 2013b)
Neurones within the primary motor cortex are organised in five histologically-defined horizontal
layers numbered with Roman numerals from superficial to deep layers (I, II, III, V and VI), each
with a characteristic cytoarchitecture and connectivity. Since the motor cortex lacks a prominent
granular layer IV which characterises the granular primary somatosensory cortex, it is referred to
as the ‘agranular’ cortex. This region corresponds macroscopically and histologically to the
coronal sections in Swanson’s rat brain atlas that are at 2.5 – 4.0 mm anterior to Bregma (Fig. 2)
(Swanson, 2004; for reviews see Asanuma, 1989; Avivi-Arber et al., 2010b, 2010c, 2015b;
Awamleh et al., 2015; DeFelipe et al., 2002; Donoghue, 1982; Kaas, 1991). Layer I lies directly
below the pia mater and the glia limitans (see below). It contains only few scattered neurones but
is abundant in horizontal reciprocal axonal projections relaying information to/from multiple
cortical (e.g., primary somatosensory cortex) and subcortical (e.g., thalamus) regions. These
axons synapse on terminals of apical dendrites of pyramidal neurones from layers III and V (see
below) (Mohan et al., 2015).
Layer I also has a small number of inhibitory neurones with GABA as their primary
neurotransmitter. Layers II-VI consist of pyramidal neurones (i.e., cortical efferent) and non-
pyramidal stellate neurones (i.e., intracortical inter-neurones). The cell bodies of the pyramidal
cells are most prominent in layers III and V. Layer III is the major target for interhemispheric
corticocortical afferents and the main source for corticocortical efferents. Layers V-VI give rise
to all of the principal cortical efferent projection to brainstem motor neuronal and inter-neuronal
regions involved in orofacial muscle control. The major descending pathway that can initiate and
influence motor activity in orofacial muscles is the so-called ‘pyramidal tract’ (i.e., ‘corticobulbar
8
tract’) with pyramidal cell bodies located mainly in layers V-VI, and efferent axons projecting
bilaterally but mainly contralaterally to synapse and activate motor neurones within the brainstem
motor nuclei. In turn, the axons of the motor neurones project via the ipsilateral motor root of the
trigeminal mandibular branch to synapse and activate the masticatory muscles including the jaw-
closing (masseter, temporalis, medial pterygoid) and jaw-opening (mylohyoid, digastric, lateral
pterygoid) muscles (Burish et al., 2008; Chen, 2004; Douglas and Martin, 2004; Iyengar et al.,
2007; Kaas et al., 2006; Mao et al., 2011; Neafsey et al., 1986; Roberts, 1986; Takata and Hirase,
2008).
Although pyramidal tract neurones can project directly to brainstem motor nuclei to directly
activate motoneurones, most of the projections related to masticatory jaw movements are
multisynaptic and project to brainstem motoneurones through other cortical or subcortical relay
regions including brainstem pre-motor inter-neurones located bilaterally at the brainstem reticular
formation regions, nucleus of the solitary tract, inter- and supra- and juxta-trigeminal regions
surrounding the trigeminal motor nucleus and mesencephalic nucleus. These brainstem pre-motor
neurones are part of the Central Pattern Generator circuitry which is a complex network of
excitatory and inhibitory inter-neurones that synapse and activate or inhibit alpha-motor neurones
within the trigeminal and other cranial nerve motor nuclei (for review, see Aroniadou and Keller,
1993; Huntley, 1997; Sessle, 2000; Sessle et al., 2013b; Westberg and Kolta, 2011)
Several features characterise the primary motor cortex in general. Nearby corticobulbar tract
neurones responsible for the contraction of different body muscles maintain their somatotopic
organisation along their efferent projection pathways. Thus, muscles that are next to each other in
the body have adjacent motor representations in the primary motor cortex known as the ‘motor
homunculus’ or ‘motor representation map’. Muscles that are involved in more complex and finer
movements have a larger motor representation within the primary motor cortex and the orofacial
muscles occupy a large motor representation area within the primary motor cortex known as the
orofacial primary motor cortex. Similar to the motor homunculus in humans, in rats, motor
representations of the body are organised in a so-called motor ‘ratunculus’ and the jaw and tongue
muscles have large motor representations within the orofacial primary motor cortex. The cortical
areas (i.e., motor representations) devoted to the motor output of each muscle in the body can be
identified, delineated and mapped by systematic spatial application of low-intensity electrical
9
currents to the cortex and recording of evoked electromyographic activity in body muscles (Fig.
2) Asanuma, 1989; Avivi-Arber et al., 2010c, 2015b; Donoghue, 1982; Neafsey et al., 1986).
It is important to note that those brain regions involved in the generation and control of orofacial
movements, including the orofacial primary motor cortex brainstem Central Pattern Generator
and motor nuclei, receive a large amount of somatosensory inputs from both sides of the orofacial
region including the teeth which can assist but also interfere with jaw movements (for review, see
Avivi-Arber, 2009, 2018; Paxinos, 2004; Sessle, 2000; 2006; Sessle et al., 2013b).
Figure 2. On the right are cortical motor maps illustrating the motor representation areas of the jaw-opening (anterior digastric) and tongue-protrusion (genioglossus) muscles within the rat left orofacial sensorimotor cortex. The motor representations are superimposed on Nissl-stained coronal hemisections of the left hemisphere at anteroposterior (AP) planes 2.4, 2.7, 3.0, 3.3, 3.6, and 3.9 mm anterior to Bregma. On the left are corresponding schematic diagrams from Swanson’s Atlas of the rat brain (Swanson, 2004) which indicate the different cortical layers in Arabic numbers (3,4,5,6). Top right of the figure is a sagittal view diagram of the rat brain. Reprinted with permission from John Wiley and Sons, Journal of Comparative Neurology, Brain maps 4.0—Structure of the rat brain: An open access atlas with global nervous system nomenclature ontology and flatmaps, Swanson L, Copyright (2018).
10
1.2.4 Clinical Implications During orofacial motor functions, such as mastication and speech production, a large number of
receptors of different types (e.g., nociceptors, thermoreceptors, chemoreceptors,
mechanoreceptors and proprioceptors) and from different orofacial tissues (e.g., skin, mucosa,
muscles, joints and teeth) are activated simultaneously and sequentially to generate patterns of
somatosensory afferent inputs to the central nervous system. Since facial and jaw-opening
muscles have significantly fewer or no muscle spindle proprioceptors, the periodontal
proprioceptors as well as the skin and joint mechanoreceptors play a crucial role in providing
peripheral feedback and feedforward information that is essential for accurate performance of
discrete as well as the complex rhythmic movements of the jaw during chewing, speaking and
other orofacial motor functions. The bilateral direct projections of primary afferent proprioceptive
neurones from jaw muscles (e.g., masseter) and periodontal ligaments to brainstem motor nuclei
are also crucial for simultaneous bilateral modulation of the masticatory muscles and for eliciting
jaw-opening and jaw-closing reflexes to protect the teeth from injury during biting, or protecting
the jaws from excessive stretching (for review see Haggard and de Boer, 2014; Paxinos, 2004;
Sessle et al., 2013b; Trulsson and Essick, 2004).
1.2.4.1 Consequences of Endodontic Treatment and Tooth Extraction The most obvious consequence of endodontic treatment is the loss of somatosensory inputs from
dental pulp primary afferent neurones (i.e., denervation) and subsequent loss of tactile,
temperature and nociceptive perception from the dental pulp. On the other hand, tooth extraction
results in denervation of both pulpal, periodontal and gingival primary afferent neuron resulting
in loss of somatosensory as well as proprioceptive inputs. Thus, tooth extraction may also impact
proprioception including perception of spatial orientation of the jaws during function and the
ability to modulate the amount of muscle force being employed during jaw movements and biting
(Trulsson and Essick, 2004).
A common consequence of both endodontic treatment and tooth extraction is the occurrence of
acute pain caused by the tissue injury and subsequent inflammatory processes that activate the
wounds and their peripheral nociceptive neurones as well as their intact neighbour neurones (Al-
Khateeb and Alnahar, 2008; Holland, 1995; Sessle, 2011a). While in most patients, postoperative
11
analgesia is effective in resolving acute pain, in a significant number of patients undergoing
endodontic treatment (5-12 %) or tooth extraction (~3%) the acute pain may develop into a
chronic pain condition. For example, Polycarpou et al. reported that 12 % of the patients receiving
endodontic treatment developed chronic pain, and Nixdorf et al. reported that in up to 5.5 % of
the endodontically treated teeth pain persisted for at least 6 months (Nixdorf et al., 2010a;
Polycarpou et al., 2005). Of note, pain by itself can cause an altered pattern of muscle activity as
well as altered cognitive motor behaviour such as favouring chewing on the painless side (Avivi-
Arber and Sessle, 2018; Lund, 2011; Sessle, 2006; Svensson and Graven-Nielsen, 2001).
Tooth extraction and subsequent reduced number of occluding pairs of teeth (but not endodontic
treatment) may also alter a subject’s preferred chewing side and alter the patterns of jaw
movements during mastication (Miehe et al., 1999; Shiraishi et al., 2017). This may affect
proprioceptive as well as mechanoreceptive inputs from muscles and other orofacial tissues
involved in jaw movements including teeth and missing teeth. Noteworthy is that even in subjects
treated with dental implant to replace the missing teeth, chewing efficiency and the ability to
adjust biting forces and muscle activity in relation to the food hardness, do not match those of
subjects with natural dentition; this may be related to the lack of periodontal ligament and sensory
inputs from periodontal receptors (for reviews see Avivi-Arber and Sessle, 2018; Trulsson and
Essick, 2012b).
Thus, any change to the dentition induced by dental treatments, including endodontic treatment
or tooth extraction, may activate or eliminate mechanoreceptive, proprioceptive and nociceptive
inputs from the teeth and surrounding tissues, and may thereby impact peripheral feedback and
feedforward information necessary for the regulation of muscles’ activity and associated
masticatory movements and biting forces.
1.3 Motor Cortex Neuroplasticity Induced by Altered Sensory Inputs and Motor Function
Numerous studies focusing on spinally-innervated tissues in animals and humans have shown that
the primary somatosensory and motor cortices involved in processing and controlling sensory-
motor functions of the limbs have a remarkable capacity to continuously form new neuronal
12
connections and re-wire their neuronal circuitry via functional and structural changes (i.e.,
neuroplasticity) in response to persistent modifications in sensory inputs and altered motor
function (Buonomano and Merzenich, 1998; Ebner, 2005). These neuroplastic changes may have
a fast- or slow-onset and may be short-lived or long-lasting. Different mechanisms may underlie
the different forms of neuroplasticity at different points of time and some may be involved
simultaneously. Fast-onset neuroplasticity, such as following peripheral denervation, can occur
within minutes and may be associated with potentiation of previously existing synapses via
unmasking of existing intracortical excitatory synaptic connections which are usually ineffective
because of inter- and intra-hemispheric lateral (e.g. GABAergic) inhibition (Farkas et al., 2000;
Jacobs and Donoghue, 1991). Long-lasting neuroplasticity may be related to enhanced or
diminished gene expression (Kleim et al., 1996), or generation of new receptors, new dendritic
branching and synapses, and even new neuron and subsequent new neuronal circuitry (Greenough
et al., 1985; Jones et al., 1996; Kleim et al. 1996, 2002, 2004; Monfils et al., 2004. Long-term
potentiation of synaptic efficacy may play a role at early and late phases of cortical neuroplasticity
(for reviews, see Boroojerdi et al., 2001; Kaas, 1991; Navarro et al., 2007).
1.3.1 Clinical Significance of Motor Cortex Neuroplasticity Most of our knowledge on motor cortex neuroplasticity comes from studies focusing on the limbs.
These studies have revealed that neuroplasticity is a crucial mechanism that can determine how
subjects adapt their motor behaviours to varying conditions, and how they learn or re-learn new
motor behaviours following injury (e.g., limb amputation) and/or rehabilitation (e.g., limb
prostheses). However, neuroplasticity may also reflect maladaptation that leads to a variety of
chronic motor as well as sensory dysfunctions (e.g., phantom limb sensation or pain, muscular
dystonia and dystrophy). Noteworthy is that the knowledge gathered from these studies in animals
and humans has influenced modern limb rehabilitation approaches which now include
neurobiologically-based approaches (for reviews, see Avivi-Arber et al., 2011b; Kleim and Jones,
2008; Sessle et al., 2013b). For example, pairing limb rehabilitation training with cortical
electrical stimulation as compared with training alone, can better enhance motor recovery
following injury (Adkins et al., 2008; Brown, 2006; Frost et al., 2003).
13
The capacity of the orofacial motor cortex to undergo functional and structural neuroplasticity is
less well-documented. Nevertheless, as with limbs motor functions, orofacial motor cortex
neuroplasticity is considered a crucial mechanism underlying orofacial motor adaptation
following intraoral injury or dental treatment, and maladaptive neuroplasticity may underlie
orofacial motor as well as sensory impairments such as phantom pain or sensation, phantom bite,
embouchure dystonia and temporomandibular disorders (Avivi-Arber et al., 2011b, 2018; Sessle
et al., 2013b). Recent electrophysiological studies in rats have shown that various intraoral
manipulation that can conceivably change sensory inputs from the orofacial tissues or alter the
chewing patterns, are associated with extensive neuroplasticity manifested as reorganisation of
jaw and tongue motor representations within the orofacial primary motor cortex (Avivi-Arber et
al., 2010b,c, 2015b; Awamleh et al., 2015; Pun et al., 2016; Sood et al., 2015). For example, acute
noxious stimulation of the dental pulp or the tongue in rats and humans have been associated with
decreased orofacial motor cortex excitability (Adachi et al., 2007; Awamleh et al., 2015;
Boudreau et al., 2007; Pun et al., 2016). In addition, it has been shown in humans, that pain can
interfere with the successful performance of a learned tongue protrusion task (Boudreau et al.,
2007). These studies suggest that the decreased cortical excitability is a mechanism contributing
to motor limitation as a protective mechanism to prevent further damage to the affected tissues
and facilitate tissue and motor recovery (for review see Avivi-Arber et al., 2011c; Sessle, 2006;
Sessle et al., 2013b).
Unilateral extraction of the rat mandibular incisor tooth was associated, one week later, with
functional neuroplasticity manifested as reorganisation of jaw and tongue motor representations
within the orofacial primary motor cortex, including a significantly increased number of jaw and
tongue sites and a significantly decreased onset latency of evoked tongue activity (Avivi-Arber et
al., 2010a). In contrast, maxillary molar tooth extraction was associated with a significant and
sustained (1-2 months) decreased number of jaw and tongue motor representations and increased
cortical excitability (Avivi-Arber et al., 2011a, 2015b). Tooth extraction can also induce structural
changes in the brain. For example, a magnetic resonance imaging (MRI) study has shown that
tooth extraction can induce widespread volumetric changes in the brain manifested as decreased
or increased volumes within several brain regions involved in processing motor information as
well as somatosensory, cognitive and emotive information (Avivi-Arber et al., 2017). Learning a
new orofacial motor task, such as tongue-force training in rats, can also induce orofacial motor
14
cortex neuroplasticity manifested as increased excitability of the primary motor cortex but with
no apparent reorganisation of the tongue motor representation (Guggenmos et al., 2009). In
contrast, training humans and non-human primates in a novel tongue-protrusion task does produce
reorganisation of the tongue motor representation in the orofacial primary motor cortex,
manifested as a significantly increased motor representation of the tongue protrusion muscle and
a decreased motor representation of the tongue-retrusion muscle (Svensson et al., 2003; Yao et
al., 2002; for review see Avivi-Arber et al. 2011a,d; Sessle et al., 2013b).
Most significant is that motor cortex neuroplasticity can be reversible. For example, dental
implant treatment that replaces missing molar teeth can reverse the changes induced by the molar
tooth extraction, but dental implants can also produce new changes that do not exist in naïve
animals and which may compensate, for example, for the missing periodontal ligament of the
missing teeth (Avivi-Arber et al., 2015b). It is also significant that motor cortex neuroplasticity
induced by acute noxious stimulation of the tooth pulp can be reversed by the application of an
astroglial inhibitor to the pial surface of the orofacial motor cortex (Awamleh et al., 2015). While
it is unclear what the exact cortical site of action of the astroglial inhibitor was in that study, it
likely diffused from the surface into the cortex to exert its effects at least on astroglial cells within
the superficial cortical layers including glia limitans and layer I. Thus, the following section
discusses astroglial structure, functions and role in motor cortex neuroplasticity.
1.4 Glial Cells Glial cells are the most abundant and diverse cell types in the brain. While there are 100 billion
neurons in the adult human brain, it is estimated that glial cells are 50 times more abundant
(Kettenmann et al., 2008). Glial cells include microglia, astroglia, and oligodendrocyte
(Gundersen et al., 2015) and this section will focus mainly on astroglia.
Oligodendrocytes can sense changes in electrical impulses in neurons and produce myelin sheath
that enwraps neuronal axons in the central nervous system and can thereby modulate the
conduction velocity of action potentials along the axons (Bradl and Lassmann, 2010; Gundersen
et al., 2015).
15
Microglia are innate immune cells in the brain which are capable of phagocytosis and
modulation of repair and scarring processes following central injury resulting in activation and
proliferation of microglia (Allen et al., 2005). Activation and proliferation of microglia have also
been observed in cortical and subcortical regions (e.g., spinal cord, brainstem trigeminal sensory
and motor nuclei) following peripheral injury including orofacial nerve injury, inflammation and
noxious stimulation of the dental pulp (Lee et al., 2010, 2011; Piao et al., 2006; Salter, 2004; Zhao
et al., 2007). Moreover, behavioural and pharmacological studies in rats (e.g., application of
microglial inhibitors to the brainstem) have shown that microglia play a crucial role in the
development of central sensitization and chronic orofacial pain as well as in modulating jaw
reflexes and chewing (Chiang et al., 2011; Hossain et al., 2017; Itoh et al., 2011; Mostafeezur et
al., 2012a,b; Sessle, 2007; Xie et al., 2007).
1.4.1 Astroglial Cells: Cytoarchitecture and Morphology There are several subtypes of astroglia, and their number, structure, morphology and function
depend on the animal species, their subtype, their location in the brain, and the developmental
stage and age of the brain. The majority of astroglial cells have a star-like shape with a cell body
and five to eight major processes, each of which is highly ramified into numerous delicate
processes.
Astroglia in layer I of the mammalian cortex are often referred to as ‘pial astrocytes’ or ‘marginal
glia’ while astroglia in the other cortical layers are collectively referred to as protoplasmic
astroglia (Bushong et al., 2004; Lanjakornsiripan et al., 2018; Pekny and Pekna, 2014). The fine
astroglial processes occupy distinct, non-overlapping domains and are in close proximity to
neuronal synapses. It is estimated that each astroglia can contact tens of thousands of synapses
(Bushong et al., 2002; Hammond, 2008; Nag, 2011) (Fig. 3).
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Figure 3. Image of GFAP-labelled astroglial cell within layer 5 of a mouse orofacial primary motor cortex obtained by 3D imaging of a 40 µm – thick brain section with a spinning disk confocal microscope (63x/1.3; water). GFAP - Glial fibrillary acidic protein, a specific marker of astroglial cytoskeleton (Unpublished data).
1.4.2 Astroglial cells: Role in Regulating Neuronal Function For many years, scientists have thought that the electrically excitable neuronal networks are
connected through chemical synapses and that the surrounding non-neuronal microglial and
astroglial cells provide only immunological and metabolic support to the neuronal functions.
However, it is now clear that glial cells play a critical role in the development and function of
neurons in the brain, and that astroglia, in particular, can sense and modulate neuronal activity
and thereby also play a crucial role in cortical neuroplasticity.
Astroglial processes are in close proximity to neuronal synapses and form the so-called ‘tripartite
synapses’, each composed of one presynaptic and one postsynaptic neuronal terminal surrounded
by astroglial processes. Synapses and astroglial process are directly connected via gap junctions
that allow for bidirectional electrical and metabolic signaling between neurones and astroglia
(Perea and Araque, 2014) (Fig. 4). Moreover, astroglia have receptors for several neuronal
mediators (including glutamate and GABA) and they can remove neurotransmitters from the
17
synaptic extracellular space. Thus, signals between neurones and astroglia occur via ion fluxes or
binding of neurotransmitters and other molecules released to/from astroglia and neuronal
synapses. Astroglial cells also form a rich network of astroglial process that are connected via gap
junctions, but inter-astroglial communication occurs through intracellular waves of calcium and
intercellular diffusion of chemical messengers. Such signals can induce or inhibit the release of
neurotransmitters and thereby affect synaptic transmission. Noteworthy is that in the brain,
astroglia are the sole source (by synthesis) of glutamine, a precursor for the major excitatory
(glutamate) and inhibitory (GABA) neurotransmitters, and inhibition of glutamine synthesis or its
transport from astroglia to neurones can affect synaptic transmission and neuronal excitability
across networks of neurones and astroglia (Araque, 2008; Awamleh et al., 2015; Ben Achour and
Pascual, 2012; Perea and Araque, 2005; Tanaka et al., 1997; Verkhratsky and Butt, 2013;
Verkhratsky and Nedergaard, 2018).
Figure 4. Schematic representation of the ‘tripartite synapse’, neuron – astroglia – neuron. Reprinted by permission from Springer Nature: Nature Neuroscience: Glia — more than just brain glue, Allen N; Barres, B, Copyright (2009) (Allen et al., 2009).
18
1.4.3 Astroglial Plasticity Another striking aspect of astroglia is their capacity to undergo short-term and long-term
functional and structural plasticity in response to sustained alterations in sensory stimuli or
trauma, inflammation, ischemia or neurodegeneration (Bernardinelli et al., 2014; Cheung et al.,
2015; Genoud et al., 2006; Perez-Alvarez et al., 2014). Dynamic cellular morphological changes
(see below) may occur in response (i.e., reaction) to increased synaptic activity, or nerve injury
which are temporally coupled with changes in intracellular Ca2+ and the release of gliotransmitters
including glutamate and GABA (Dallerac et al., 2013; Eng et al., 1992; Newman, 2003).
Astroglial structural responses to injury may include: (1) proliferation, movement and
differentiation; (2) upregulation of Glial Fibrillary Acidic Protein (GFAP), the main astroglial
intermediate filament protein used as a specific marker to identify astroglial cytoskeleton,
(Bignami and Dahl, 1977; Garcia-Cabezas et al., 2016); (3) changes in shape, volume,
cytoskeletal organisation, lysosomal fragility, and enzyme content. (Eng et al., 1992; Pekny and
Pekna, 2014; Sun and Jakobs, 2012; Yu et al., 2012).
Similar to neuroplasticity, such a remarkable astroglial plasticity may underlie the functional
adaptation (or maladaptation) of neurones and behaviour following injury and treatment
(Verkhratsky and Nedergaard, 2018). Interestingly, evidence from the last decade has shown that
astroglia in rodent brainstem play a crucial role in acute and chronic orofacial pain conditions,
and that they can undergo functional and structural changes under these conditions (Chiang et al.,
2012, 2007; Mostafeezur et al., 2014; Okada-Ogawa et al., 2015; Sessle, 2007; Tsuboi et al., 2011;
Xie et al., 2007). However, little is known of the effects of tooth extraction and endodontic
treatment on the structure and function of astroglia in the orofacial primary motor cortex.
1.5 The CLARITY Technique Conventional immunofluorescence methodologies have been used for high-resolution
visualisation of structural, morphological, connectivity and organisational features of different
cells in thin (µm) serial sections of the brain. Traditionally, only a certain number of sections are
included for high-resolution imaging and subsequent analysis of specific regions of interest in the
brain. Main disadvantage of this technique is the loss of information and the difficulty to achieve
19
3D high-resolution image of the cytoarchitecture of a whole few millimeter-thick brain tissues.
While inclusion of all sections for 3D reconstruction is available, it requires sophisticated image
stitching techniques and is very labor intensive and expensive, and thus is usually limited to very
small volumes of tissue, measured in a few microns. Moreover, mounting sections on slides
renders the method irreversible and thus the slightest mistake in the process can ruin the whole
samples or even the whole experiment.
Over the last few years, several optical clearing and imaging techniques have been developed to
overcome the limitations of the conventional immunohistochemical techniques. These new
techniques allow for high-resolution 3D cytoarchitectural visualisation of intact, several mm-thick
brain sections, and even a whole intact mouse or rat brain (Chung and Deisseroth, 2013; Chung
et al., 2013; Tomer et al., 2014). One of these clearing techniques is the Clear Lipid-exchanged
Acrylamide-hybridized Rigid Imaging-compatible Tissue-hYdrogel (CLARITY) (Chung and
Deisseroth, 2013; Costantini et al., 2015; Jensen and Berg, 2016; Tomer et al., 2014) (and see:
http://clarityresourcecenter.org; http://wiki.claritytechniques.org).
This technique utilises optically transparent porous hydrogel matrix that is perfusion-infused into
the tissues to provide a substructure that links tissue-proteins, nucleic acids and other
biomolecules together while dissolving and clearing the tissue of its lipid content (See Fig. 8 in
Chapter 2). The resultant hydrogel-tissue hybrid provides physical support to fine structures of
the brain and preserves their cytoarchitecture and molecular information during the subsequent
step in which a chemical detergent is used to clear the tissue from lipids that otherwise would
cause light scattering and prevent penetration of large molecules. This tissue-clearing process
results in an optically-transparent and macromolecule-permeable tissue that allows deep
penetration of light and macromolecules (e.g., antibodies and fluorescent markers); the light can
excite fluorescent-labelled cells and molecules, the signals of which can be captured with a camera
to produce 3D image of thick intact-tissue architecture with minimal light-scatter artifacts.
The original CLARITY technique utilises electrophoresis for tissue-clearing (ETC) to expedite
the lipid removal from brain tissue. For example, a whole mouse brain can be cleared overnight.
However, main disadvantages of ETC include the complexity of the technique, ability to clear a
limited number of brains at one time (i.e., it depends on the number of available electrophoresis
20
systems), and distortion of brain tissue (Tomer et al., 2014; Zheng and Rinaman, 2015). An
alternative to the ETC is the passive tissue-clearing technique that is carried out in a temperature-
controlled shaker. This technique can overcome the limitations of the ETC, and it also eliminates
the need to use electrophoresis equipment (Spence et al., 2014; Tomer et al., 2014; Yang et al.,
2014). Even though passive clearing requires a significantly increased clearing time (e.g., few
months for a whole mouse brain), immunolabelling seems to work best in samples that have been
passively cleared as opposed to ETC (http://wiki.claritytechniques.org).
1.6 Light-Sheet Fluorescence Microscopy Another important advancement in brain imaging was applying light-sheet fluorescence
microscopy to cleared brains (Dodt et al., 2007; Stefaniuk et al., 2016; Tomer et al., 2014). By
scanning the sample volume plane-by-plane instead of point-by-point, light-sheet allows for fast
imaging of large specimens with sufficient resolution for quantitative neuroanatomy (Silvestri et
al., 2015). It utilises a rapid and precise (high spatial and temporal resolutions) visualisation of
multiple fluorescently-labeled components at the tissue, cellular or molecular levels. Another
advantage of the light-sheet is the minimal imaging-related photobleaching (from
http://blogs.zeiss.com) (Selchow, 2013) (Fig. 5). Although light-sheet imaging provides essential
structural information, the images are not pristine and often contains dark stripes (see Chapter 2).
Such artifacts generically arise from either absorbing or scattering structures along the
illumination light path (Becker et al., 2008; Santi, 2011).
21
Figure 5. A-C. Layout of the light-sheet Z.1 fluorescence microscope. The objective lens and detection beam-path are perpendicular to the illumination beam-path. A laser light that is formed into a thin sheet of light illuminates the fluorescently-labeled tissue from either one or two sides. This illumination excites only fluorophores within the focal plane of the detection objective. All fluorescent signals are collected on a camera-based detector. D-E. The light-sheet is generated either statically by using a cylindrical lens or dynamically by high-frequency scanning of a laser beam. Reprinted by permission from Zeiss: https://www.zeiss.com/content/dam/Microscopy/Products/imaging-systems/Lightsheet%20Z1/photonik_intl_2013_01_044_HiRes.pdf
1.7 Statement of the Problem, Hypothesis and Objectives Following tooth extraction and endodontic treatments, many patients will suffer from orofacial
sensory and/or motor impairments for short or long term. While the underlying mechanisms are
unclear, novel data suggest that they may involve the orofacial primary motor cortex, the main
brain region involved in sensory-motor control and integration. Our group has shown that intraoral
manipulations in rodents, such as orthodontic treatment, tooth trimming or extraction, dental
implant surgery and acute noxious stimulation of the dental pulp, can induce functional changes
in the orofacial primary motor cortex and these changes may involve and be dependent on the
functional integrity of astroglial cells. Astroglia regulate neuronal function at synapses, and
astroglial process are directly connected with neurones, allowing bidirectional electrical and
metabolic signaling between neurones and astroglia. It is well documented that changes in
astroglial function are tightly coupled to changes in their morphology and in their expression of
22
GFAP. However, no study has tested whether endodontic treatment versus tooth extraction can
produce morphological changes in astroglial cells within the orofacial primary motor cortex.
Conventional immunohistochemistry uses a certain number of thin (μm) sections out of the whole
specimen. This may result in a loss of information and the inability to achieve 3D high-resolution
image of the cytoarchitecture of a whole few millimeter-thick brain tissue. Moreover, mounting
sections on slides renders the method irreversible and thus the slightest mistake in the process can
ruin the entire samples. Novel optical clearing techniques have been developed to overcome these
limitations. The Clear Lipid-exchanged Acrylamide-hybridized Rigid Imaging-compatible
Tissue-hYdrogel (CLARITY) technique renders the brain optically transparent and allows for
high-resolution 3D cytoarchitectural visualisation of cellular morphology and spatial interactions
across different cell types within an intact, several mm-thick brain sections, and even a whole
intact mouse or rat brain. This technique has not been utilised previously in oral neurophysiology
research.
Better understanding of the role and involvement of astroglia in orofacial motor functions in
health and disease is of clinical significance since it can assist in the development of improved
therapeutic approaches of orofacial motor impairment such as targeting astroglia within the
orofacial motor cortex.
1.8 General Aim The general aim of the present thesis was to use an animal model and the novel CLARITY
technique for 3D characterisation of astroglial cytoarchitecture and quantification of
morphological changes in astroglial cells within thick brain sections of the orofacial primary
motor cortex of rats receiving tooth extraction or endodontic treatment.
1.9 Hypothesis Extraction but not endodontic treatment of three right maxillary molar teeth induces, within one-
week, changes in the morphological features of astroglial cells within the superficial layer I of the
rat orofacial primary motor cortex.
23
1.10 Specific Aims 1. To use 2 mm-thick coronal brain sections and optimise the novel CLARITY
immunohistochemistry technique to allow for 3D characterisation of astroglial and
neuronal cytoarchitecture and morphology within the superficial layers of the rat orofacial
primary motor cortex.
2. To test if endodontic treatment versus extraction of three right maxillary molar teeth can
induce within one-week changes in the morphological features of astroglial cells in the
superficial layer I of the rat orofacial primary motor cortex.
24
Materials and Methods
All experimental procedures were approved by The University of Toronto Animal Care
Committee, in accordance with the Canadian Council on Animal Care Guidelines and the
regulations of The Ontario Animals for Research Act (R.S.O 1990). The experiments reported
herein followed a strict standard protocol and all experimental procedures were carried out by the
same investigator to ensure consistency and uniformity of the procedures. Data analysis was
carried out in a blinded manner to reduce potential experimenter bias.
2.1 Animals The present study was carried out on young adult male Sprague-Dawley rats (Charles River,
Montreal, QC, Canada). Rats were 225-250 g upon arrival to the vivarium, and 300-340 g on the
day of perfusion. All rats received a basic health assessment upon arrival (weight, skin, eyes, teeth
and fur inspection). Consistent with our published (Avivi-Arber et al., 2010a, 2015b) and ongoing
studies, rats were single-housed (27 x 45 x 20 cm cages) to minimise social effects that might
mask treatment outcome (Devor et al., 2007; Seminowicz et al., 2009). The cages contained a
polyvinyl chloride tube (used as a shelter and a gnawing device) and were stored under the same
temperature (21 ± 1 °C) and humidity (50 ± 5 %) controlled conditions and a 12-hour light/dark
cycle (lights on at 07:00, off at 19:00 h). Consistent with our ongoing studies involving intraoral
manipulations, all rats received mash chow diet and water ad libitum to avoid postoperative
discomfort from biting on a hard diet and to ensure adequate food and drink intake. Consistent
with the literature and our previous studies, since transportation and changes in husbandry
environment are potentially stressful events that can significantly impact animals’ health and
function which may impact treatment effects on brain functions, all rats were subjected to a 7-day
acclimation period (Fig. 7). Rats were monitored daily to assess body weight, food consumption
and any change in their grooming, scratching or exploratory behaviour.
25
2.2 Study Groups and General Study Design
A total number of four rats were used to optimise the CLARITY and immunofluorescence
technique. A total number of 28 rats were used to test whether tooth extraction versus endodontic
treatments can induce, one week later, differential changes in the morphological features of
astroglial cells within the rat orofacial primary motor cortex. The one week time point was chosen
since previous studies have shown that animals develop postoperative perioral hypersensitivity
that peaks between postoperative day four and seven and thereafter subsides and returns to
baseline within 14 days (Lakschevitz et al., 2011).
To prevent allocation bias, rats were randomly allocated into control and experimental groups
(n=7/group). Rats of the extraction (‘Exo’) group received extraction of the three right maxillary
molar teeth and rats of the endodontic (‘Endo’) group received endodontic treatment in the three
right maxillary molar teeth. Rats of the ‘Sham’ group received the same general anaesthesia and
mouth opening as the Exo and Endo groups but without actual tooth extraction or pulpectomy.
Rats of the ‘Naïve’ group received no treatment and no anaesthesia. Consistent with previous
studies and to reduce postoperative pain and inflammation, rats received analgesics and anti-
inflammatory drugs for the first three postoperative days. Rats were perfused on postoperative
day seven (Fig. 6). Brains were extracted and thereafter 2 mm-thick coronal sections containing
the orofacial motor cortex went through clearing and subsequent immunohistochemistry
procedures to label astroglial cells. We also immunolabelled cellular nuclei and neuronal nuclei
to assist in identifying the superficial layer I. 3D imaging was carried out with a light-sheet Z1
fluorescence microscope (Carl Zeiss, Jena, Germany) (20x CLARITY objective). Images were
then processed with Bitplane Imaris software to automatically identify and quantify
morphological features of astroglial processes.
26
Figure 6. Experiment time-line. Rats were monitored on a daily basis from the date of arrival at the vivarium until perfusion day. Weight (yellow arrow) was measured on arrival, after acclimation period and on the day of perfusion. Treatment (endodontic treatment, tooth extraction or sham operation) were carried out following a 1-week acclimation (green band). Analgesics and anti-inflammatory drugs were administered up to three days postoperatively (pink band). Perfusion was performed on day 7 after treatment (blue band).
2.3 Animal Experiments
2.3.1 Anaesthesia and Aseptic Procedures
All surgical procedures were carried out under standard aseptic surgical conditions with
isoflurane/oxygen for general anaesthesia (1-3% Isoflurane; 1L/min mixed with O2)
supplemented with local infiltration of lidocaine hydrochloride 0.1 ml, 2% in 1:100,000
epinephrine (Lignocaine, Lignospan standard®, Septodont, Ontario, Canada) injected to the labial
and palatal sides of the three right maxillary molar teeth. Pulse oximeter monitoring verified that
the heart rate and oxygen saturation levels were within a physiological range (i.e., 333–430
beats/min, 90-100% O2). A controlled heating pad (Model 73A, YSI, Ohio, USA) maintained the
rat core temperature at 37–37.5°C, and their eyes were treated with a lubricating ophthalmic
ointment (Alcon®, Novartis, Canada). All the instruments used during the procedures were
sterilised in an autoclave at 121o C.
2.3.2 Tooth Extraction, Pulpectomy and Sham Operations
Dental surgeries and sham operations were carried while the animal was under general anaesthesia
(see above), lying in a supine position with a mouth being kept opened by pulling down the 2
mandibular incisors with a dental floss. The tongue was fixed to the left cheek with a tape (Fig.
7A). The surgical area was wiped using a cotton applicator soaked with 0.12% chlorhexidine
27
gluconate (Peridex®, 3M ESPE, Canada), and a gauze was placed at the back of the throat to
protect the rat from any aspiration. Thereafter, a local anaesthetic was injected into the palatal
gingivae and buccal vestibule. All surgical procedures were carried out with the aid of an optical
magnification of 4.5x using dental loupes (Orascoptic, Middleton, WI, USA).
2.3.2.1 Tooth Extraction
The marginal gingiva around the three right maxillary molar teeth was gently detached. Then, the
teeth were luxated using modified dental instruments (Avivi-Arber et al., 2015b, 2017).
Hemostasis was achieved by applying pressure to a sterile gauze pressed over the extraction
sockets for a few minutes (Fig. 7C).
2.3.2.2 Endodontic Treatment
Surface disinfection of the three maxillary molar teeth was carried out with 2.5 % sodium
hypochlorite. The area was kept dry by continuous suctioning and application of a cotton roll to
the buccal vestibule. For dental pulp extirpation, occlusal access cavities were drilled using a low-
speed handpiece and a LN 25 carbide bur (Dentsply Maillefer, Ballaigues, Switzerland). Root
canals were identified and cleaned using a filing motion with K-files #10; 21 mm long, bent at
2.5 mm from the tip, (Dentsply Maillefer, Ballaigues, Switzerland) and irrigated with 2.5%
NaOCL under continuous suction (BabySmile S-502 Nasal Aspirator). When there was no more
bleeding from the canals, final irrigation with 2.5 % sodium hypochlorite for 1 minute per tooth
was performed (Fig. 7D). Canals were dried with paper points and the pulp chamber was filled
with an aqueous paste of calcium hydroxide (Vista Dental Products, Racine, WI, USA). The
access cavity was sealed with IRM dental filling (Dentsply Maillefer, Ballaigues, Switzerland).
2.3.2.3 Sham Operation
Sham rats had exactly the same surgical operation as rats of the Exo and Endo groups including
general and local anaesthesia, analgesics and anti-inflammatory drugs, and mouth opening for 30-
60 min, and kept for a similar period of time that was used for the pulpectomy and extraction
28
procedures of the Exo and Endo groups. However, no actual tooth extraction or endodontic
treatment was carried-out in Sham rats.
Figure 7. A. Mouth opening. B. Maxillary molar teeth. C. Extraction sockets of right maxillary molar teeth. D. Access cavities for dental pulp extirpation of right maxillary molar teeth. E. Radiographic image of the right maxillae showing maxillary molar teeth after pulpectomy and restoration of access cavity with a temporary filling material. F. Radiographic image of the right maxillae showing extraction sockets.
2.3.2.4 Postoperative Care
After the surgical operation, rats were placed back into their cage under a heat lamp and monitored
for 30 mins to ensure complete recovery from the general anaesthesia. Rats are known to develop
periapical inflammatory changes after pupal extirpation (Holland, 1995). Whereas after tooth
extraction they may develop postoperative perioral hypersensitivity that peaks between
postoperative day 4 to 7 and thereafter subsides and returns to baseline within 14 days
(Lakschevitz et al., 2011). Therefore, to reduce postoperative pain and inflammation following
the surgical operations, buprenorphine hydrochloride (0.05 mg/kg, s.c., Buprenex, Reckitt
Benckiser Healthcare Ltd, USA) and ketoprofen (5 mg/kg, .c., Anafen ® Injection, Boheringer
Ingelheim, Canada) were administered subcutaneously every 8–12 h during the first three
postoperative days. This postoperative care procedure was consistent with previous studies
(Avivi-Arber et al., 2010a, 2015b; Avivi-Arber et al., 2017). Consistent with previous studies,
rats recovered uneventfully following the endodontic treatment (Erausquin and Muruzabal, 1967;
1968; 1969) and tooth extraction surgery (Avivi-Arber et al., 2015b). Following the operations,
rats showed a normal feeding, grooming, scratching and exploratory behaviours, and a normal
mean of daily rate of body weight gain.
29
2.4 The CLARITY Immunhistochemistry Technique All the procedures described below and summarized in Figure 8 were adapted from the CLARITY
Protocol developed by Karl Deisseroth’s Lab at Stanford University (Deisseroth, 2017; Engberg,
2014). Some modifications were introduced to optimise tissue-clearing and immunolabelling of
astroglial cells as well as neurones within the orofacial primary motor cortex, our region of
interest.
2.4.1 Hydrogel Monomer Perfusion-Infusion General anaesthesia was induced with Ketamine HCl (175 mg/kg, Ketaset®, Ayerst Veterinary
Laboratories, Ontario, Canada; I.M) and Xylazine (25 mg/kg, Rompun®, Bayer, Ontario, Canada).
A deep state of anaesthesia was confirmed by the lack of a twitch in response to a strong pinch of
the hindlimb. The rat was then placed on its back on the dissection pad in a supine position. A
transverse incision was made with scissors first through the skin just below the ribs and then
through the abdominal wall and ribs. Care was taken not to damage large blood vessels or organs
such as the lungs and liver. The pericardium was gently detached from the heart. The anterior wall
of the chest was raised and flipped backwards to keep the heart exposed. A metal perfusion needle
with a ball tip was inserted through the apex of the left ventricle into the aorta. When placed
correctly, the tip of the perfusion needle was visible through the transparent wall of the aorta. The
needle, just below the ball tip, was then secured to the aorta wall with a silk suture. Then, the right
atrium was cut open and 200 mL of ice-cold (4 °C) 1X PBS solution wasere perfused with a
peristaltic pump (10 ml/min, ~5 - 10 min) through the needle and the right aorta to clear all blood
from the capillaries in the brain and other body tissues. This step was followed by perfusion
(10ml/min, ~5-10 min) of 200 ml of ice-cold fixative hydrogel solution (Fig. 8, Table 1).
Adequate perfusion was confirmed by the appearance of a pale-color liver and a stiff tail
(http://wiki.claritytechniques.org).
30
Figure 8. Overview of the CLARITY technique. Step 1- Hydrogel monomer perfusion-infusion: An optically transparent porous matrix composed of formaldehyde (red), acrylamide and bisacrylamide (hydrogel) monomers (blue), and thermally-triggered initiators, is perfusion-infused into the brain tissue at 4 oC. The formaldehyde forms crosslinks with the tissue, and covalent links (electron sharing) between the hydrogel monomers and tissue-proteins, nucleic acids and other biomolecules. Step 2- Hydrogel tissue embedding: At 37 oC, the tissue-bound monomers polymerise and create a hydrogel mesh–tissue hybrid that provides physical support to tissue structure. Step 3- Passive clearing of membrane lipids: Passive clearing removes lipids and molecules that remained unbound to the hydrogel. While detergent (sodium dodecyl sulfate, SDS) micelles diffuse passively through the tissue, they capture and clear out lipid of the tissue. The hydrogel–tissue hybrid keeps biomolecules and fine cytoarchitectural features of the brain intact, including neuronal and glial proteins. Despite clearing, some light-scattering remains due to heterogeneous distribution of proteins and nucleic acid complexes in the hybrid. Step 4- Standard immunolabelling of cells or molecules. Step 5- Optical clearing and refractive index matching: Immersion in 2,2'-thiodiethanol (TDE) solution for: optical clearing; tissue shrinkage to compensate for clearing-induced tissue expansion; refractive index homogenization. Step 6- Image acquisition: Light-sheet microscopy to visualise cells in intact thick tissue. Adapted by permission from Springer Nature: Nature Methods. CLARITY for mapping the nervous system, Chung, K; Deisseroth, K, Copyright (2013) (Chung and Deisseroth, 2013).
31
Table 1. List of Solutions, ingredients and manufacturer.
Formalin and acrylamide are toxic and irritant chemicals. ❌Sodium dodecyl sulfate (SDS), boric acid and TDE are irritant chemicals, therefore all experimental steps utilising these chemicals were carried-out in a fume hood with appropriate personal protective equipment (i.e., gloves, lab coat, safety glasses, and shield).
2.4.1.1 Brain Dissection
Immediately following the perfusion, the fixed brain was extracted from the skull. The skin,
connective tissue and muscles surrounding the skull were cut and removed with scissors and a
rongeur instrument, the first spinal vertebrae was cut out, the spinal cord was cut with the tip of
Use/ Solution Ingredients Manufacturer Perfusate Saline Solution.
- 200 mL (for 1 rat)
1X PBS – 200 mL
Life Technologies
Fixative and substructure Hydrogel Solution.
- 400 mL (for 2 rats)
Acrylamide (40% v/v) - 40 mL Bis-Acrylamide (2% v/v) - 10 mL Buffered Formalin Sol. 10% v/v - 100 mL VA-044 Initiator - 1 g (0.25 w/v) 10 X PBS - 40 ml Deionised water - 210 ml
Bio-Rad Bio-Rad EM Sciences WAKO BioShop
Storage Phosphate Buffered Saline Triton (PBST) 1 L (for 40 brains)
PBS 1X - 1L Triton-X 100 0.1% v/v - 1mL Sodium Azide - 0.1% w/v - 1 gr
Life Technologies BioShop Sigma
Clearing Buffer Solution - 10 L (for 56 brains)
Boric Acid - 123.66 g Deionised water - 2L Sodium hydroxide (NaOH)
– adjust pH to 8.5 Sodium dodecyl sulfate (SDS)❌
– 4% w/v-400mg Deionised water - up to 10 L
BioShop BioShop Invitrogen
Buffer Wash Phosphate Borate Triton (PBT)
- 1L (for 6 brains)
Boric acid - 12.5g ❌ Deionised water - 1L Sodium hydroxide (NaOH)
– adjust pH to 8.5 Triton-X 100 0.1% - 1 mL Sodium Azide 0.1% w/v - 1 g
BioShop BioShop BioShop Sigma
Refractive Index Matching & Optical Clearing 30% 2,2′-Thiodiethanol (TDE ❌
- 100 mL (for 4 brains) 63 % TDE ❌
- 100 mL (for 4 brains)
TDE – 30 mL PBS 1X – 70 mL TDE 63 mL PBS 1X 7mL
Sigma Life Technologies Sigma Life Technologies
32
fine scissors at the level of C2, then the rongeur was used to fracture the zygomatic arches, remove
the auditory meatuses, and then to gently remove the skull from around the brain starting at the
ventral surface of the skull, then going lateral and rostral. Then the brain was gently lifted to allow
for optical chiasm transection and trimming of any dura connecting the brain to the skull.
Thereafter the olfactory nerves were transected, and the brain was gently lifted and removed out
the skull. Special care was taken not to damage the motor cortical areas.
In addition, the rat maxillae were collected into 50 ml Falcon conical tubes containing 10 ml of
10% buffered formalin solution for radiographic evaluation of extraction sites and periapical
tissue (Fig. 7 E, F).
2.4.1.2 Hydrogel Tissue Embedding
Each brain was placed in a 50 ml conical Falcon tube containing 25 mL of ice-cold hydrogel
solution and stored at 4 °C for 7 days to allow further diffusion of the hydrogel solution into the
brain tissue.
2.4.2 Hydrogel Tissue Hybridisation
The Falcon tube with a loosened lid was placed in a desiccation chamber (in a fume hood) hooked
up to a carbon dioxide tank and a vacuum pump (two Falcon tubes at a time). A vacuum was
applied to the chamber for 20 minutes to remove all oxygen (i.e., ‘degassing’) which was then
replaced with inert 100% carbon dioxide gas flowing into the chamber for three minutes. Then,
the Falcon tube was quickly sealed to prevent reintroduction of oxygen. The tube was submerged
in a temperature-controlled 37oC water-bath for 3-4 hours to polymerise and crosslink the
hydrogel matrix.
After polymerisation, the gel was peeled off from the brain with a lint-free tissue paper
(KIMTECH Science®, Kimberly-Clark, Canada) and stored individually in a labelled 50 mL
Falcon tube with PBST solution until ready for sectioning. A mark was made to the right side of
the brain to differentiate it from the left side. We used macroscopic anatomical features of the
brain to determine the location of the orofacial primary motor cortex, corresponding to Swanson’s
33
atlas location ~2 – 4 mm anterior to Bregma (see Chapter 1 Fig. 2) (Swanson, 2004). The 2-
millimeter thick coronal sections containing the orofacial primary motor cortex were cut with a
vibratome 3000 (Model 3000, TPI, Missouri, USA). Each 2-mm thick section was stored in 50 ml
Falcon tube with 25 ml of PSBT solution (Table 1) until ready for passive tissue-clearing.
2.4.3 Passive Tissue-Clearing of Membrane Lipids
Passive clearing of membrane lipids from each of the 2 mm-thick coronal section was carried-out
by sequential immersions in a clearing solution (Table 1) within a 50 mL Falcon tube placed on
a 3D Rotator platform (30 RPM, LAB-LINE) and incubated at 45 °C. The section was first washed
in 50 mL clearing solution for one day, and then for additional two days in fresh clearing solution
to remove excess of formalin, initiator, and hydrogel monomers. Subsequently, 50 ml of fresh
clearing solution was changed every two days. The clearing was checked visually by holding the
container up to the light until all lipids solubilised rendering the tissue completely transparent
(i.e., ‘see-through’ tissue) for microscopy (Engberg, 2014) (Fig. 9). Clearing took approximately
15 days.
Figure 9. A. A whole brain after hybridisation. Dotted lines mark the region of 2 mm-thick coronal section containing the orofacial primary motor cortex. B. Rostral view of a 2 mm-thick coronal section. C. Rostral view of a 2 mm-thick coronal section after 7 days of passive clearing. D. Rostral view of a 2 mm-thick coronal section following ~15 days of clearing; the tissue appears clear and ‘see-through’. Notice the significant increase in the size due to swelling that occurred during the passive clearing.
2.4.3.1 Buffer Wash and Storage
Following clearing, each section was placed in 50 mL buffer wash made of Phosphate Borate
Triton (PBT) solution (Syed et al., 2017) (Table 1) in a Falcon tube placed on a 3D rotator platform
34
(30 RPM, LAB-LINE) at room temperature to wash out SDS micelles. The PBT was replaced
three times per day for two days, and thereafter, the sections were stored in PBT solution at 4 °C
until tissue labelling.
2.4.4 Immunolabelling: Optimisation Protocol for Whole-Tissue
The focus of this step was to optimise the immunolabelling of astroglial cells with a specific glial
fibrillary acidic protein (GFAP) antibody to allow for subsequent characterisation and
quantification of morphological features of astroglia within 2 mm-thick cleared motor cortex brain
sections (Table 2) (Bastrup and Larsen, 2017; Bignami and Dahl, 1977; Chung and Deisseroth,
2013; Chung et al., 2013; Costantini et al., 2015; Eng et al., 2000; Garcia-Cabezas et al., 2016;
Tomer et al., 2014) (http://wiki.claritytechniques.org/index.php/Immunostaining). In addition, we
used and optimised immunolabelling of a neuronal nucleus marker (NeuN) that is known as a
Fox-3 protein, which is expressed exclusively by neurones and plays a role in regulating neuronal
cell differentiation and nervous system development (Kim et al., 2009). NeuN is conventionally
applied to distinguish astroglia from neurones and was used in this study assist in delineating the
cortical layer I (Gusel'nikova and Korzhevskiy, 2015; Mullen et al., 1992).
We also used and optimised the immunolabelling with 4′,6-diamidino-2-phenylindole (DAPI),
which is a blue-fluorescent DNA stain that is commonly used as a nuclear counterstain in
fluorescence microscopy. DAPI has high affinity for DNA and has been used, for example, to
count cells and sort them based on DNA content, or to measure cell apoptosis.
We have used Alexa Fluor-conjugated antibodies as primary antibodies that are already directly
conjugated to a fluorophore-coupled secondary antibody, thus eliminating the need for incubating
the primary antibody with a secondary antibody. This simplified and shortened the
immunolabelling process since there was no secondary antibody incubation step, needing fewer
washing steps. Conjugated antibodies are also cheaper. In addition, to save on material and
incubation time, in the optimisation process we used 200 μm-thin coronal sections.
2.4.4.1 Whole-Tissue Immunolabelling Protocol
The 2 mm-thick sections were cut in the midline to separate the left and right hemispheres. Only
the left hemispheres contralateral to the dental manipulation side were collected for
35
immunolabelling since it has previously been documented that while orofacial muscles and tissues
have bilateral representations within the orofacial motor cortex, the contralateral representations
are significantly more predominant. Moreover, unilateral orofacial manipulations, such as tooth
extraction, induce functional neuroplasticity mainly within the contralateral orofacial motor
cortex (Adachi et al., 2007; Avivi-Arber et al., 2010b, 2015b).
Brain sections were transferred into new 50 ml Falcon tubes containing 0.5 mL PBST solution of
1:70 (7.1µl) anti-GFAP antibody conjugated to Alexa Fluor® 488, anti-NeuN antibody
conjugated to Alexa Fluor® 555 and DAPI (Table 2). Tubes were placed on a rotating platform
(at 30 RPM) and incubated at 37 °C for 6 days. Tissue sections were then washed in PBST at
37 °C for 6 days, changing PBST twice during working hours (i.e., 9 am and 6 pm). From this
stage forward, the Falcon tubes were tightly covered with aluminum foil to protect the
fluorescence antibodies from light and prevent fading (photobleaching) of the fluorophores.
Antibodies come in small amounts within small vials that were centrifuged before aliquoting to
ensure all the material was at the bottom of the vial available for use.
Table 2. List of conjugated antibodies used for immunolabelling.
Antibody Target Manufacture Catalog number
Wavelength Excitation (nm)
Wavelength Emission (nm)
Concentration/ 500 µL PBST
Anti-Glial Fibrillary Acidic Protein (GFAP)
Alexa Fluor® 488 Conjugate
Astroglial filaments
Sigma MAB3402X 493 (Green)
519 (Green)
1:70
7.1 µL
Anti-NeuN clone A60 Alexa Fluor® 555
Conjugate
Neuronal nuclei
Sigma MAB377A5 555 (Red)
565 (Red)
1:70 7.1 µL
4,6-Diamidino-2-
phenylindole dihydrochloride (DAPI)
Nucleic acid all cell
nuclei
AAT Bioquest
17510 (AAT) 356 (Blue)
461 (Blue)
1:70 7.1 µL
2.4.5 Optical Clearing and Refractive Index Matching
A transparent brain tissue immersed in a solution of the same refractive index as its internal
refractive index will appear invisible. Thus, the refractive index of the brain section had to be
36
equilibrated to that of the imaging immersion medium, which in turn had to be matched as closely
as possible to the refractive index of the imaging objective (Richardson and Lichtman, 2015). The
objectives of the light-sheet Z1 fluorescence microscope (Carl Zeiss, Jena, Germany) have a
refractive index 1.45 which is suitable for imaging cleared tissue at a high-resolution.
FocusClear is a recommended immersion solution in the original CLARITY protocol, and in
particular for thick-tissue sections like a whole mouse brain. FocusClear has shown to provide the
optimal optical transparency and maximum imaging depth (Tomer et al., 2014). However, it is an
extremely expensive solution ($180 USD/ 5 ml). Other more affordable solutions with a RI of
~1.45, such as glycerol 87% (Tomer et al., 2014) and 63% 2,2′-thiodiethanol (TDE) (Costantini
et al., 2015; Jensen and Berg, 2017), can also be used but only for imaging thin tissue sections (<
1- 2 mm thick) or for a small imaging depth (http://wiki.claritytechniques.org). Thus, glycerol and
TDE were tested in this study to obtain the best tissue transparency and maximum imaging depth.
GFAP- and NeuN-labelled sections went through serial incubations in series of TDE or glycerol
solutions (Table 3).
For glycerol, the sections were incubated in different concentrations of the solution incrementally.
First, the brain section was placed in 50 mL 25% (vol/vol) glycerol in 1X PBS (Glycerol/PBS)
and stored in a Falcon tube on a 3D rotating platform (30 RPM) at 37 °C for 1 day (~24 hrs).
Then, the sample was transferred to a new Falcon tube containing 50 mL 50% (vol/vol) glycerol
in 1X PBS and stored in the same conditions as before. Lastly, the sample was transferred to a
new Falcon tube containing 87% (vol/vol) glycerol in 1X PBS and stored at the same conditions
as before and imaging was performed the following day (Tomer et al., 2014).
(http://wiki.claritytechniques.org/index.php/Solutions). With glycerol, the sections remained
visually cloudy and this resulted in less penetration depth and less image quality.
For TDE, the sample was immersed in 50 mL of 30% (vol/vol) TDE in 1X PBS (TDE/PBS) (pH
7.5) and stored in a Falcon tube placed on a 3D rotating platform (30 RPM) at 37 °C. The section
remained in the 30% TDE until its internal region got saturated with TDE as evident by its sinking
to the bottom of the tube (~1.5 hrs). Then, the section was immersed in 50 mL 63% (vol/vol) TDE
in the same conditions as before and until the section sunk to the bottom of the tube (~1.5 hrs).
After immersion in TDE, the sections became completely transparent but acquired a yellow hue.
37
Sections also shrunk in TDE which appears to compensate for the swelling occurring following
tissue-clearing (Costantini et al., 2015; Epp et al., 2015).
We found that TDE, as compared with glycerol, provided a simpler and faster procedure for
refractive index matching and optical clearing, and it also allowed for acquiring images with a
deeper penetration depth and a higher resolution. Therefore, 63% TDE was used as the immersion
solution for this study.
To further minimise refractory index mismatch and subsequent optical errors such as spherical
aberrations (https://photographylife.com/what-is-spherical-aberration), and to improve the image
quality and penetration depth, before each brain imaging the refractive index of the immersion
solution (63% TDE) was checked with a refractometer to ensure it is within 1.45 ± 0.03 (Fig. 10).
Figure 10. Refractometer. Prior to the light-sheet imaging, a refractometer was used to ensure that the Refractive Index (RI) of the 63% TDE immersion solution matches the refractive index of the light-sheet imaging objective (i.e., 1.45).
Table 3. Testing options for optical clearing and refractive index matching
Solutions Volume Concentration Rotation Temperature Time
Glycerol/PBS 50 mL 25% 30 RPM 37 °C 24 hrs
Glycerol/PBS 50 mL 50% 30 RPM 37 °C 24 hrs
38
Glycerol/PBS 50 mL 87% 30 RPM 37 °C 24 hrs
TDE/ 1X PBS 50 mL 30% 30 RPM 37 °C Until sunk to the bottom of
the tube (~1.5 hrs )
TDE/ 1X PBS 50 mL 63% 30 RPM 37 °C Until sunk to the bottom of
the tube (~1.5 hrs )
2.4.6 Whole Tissue Imaging
2.4.6.1 Mounting Cleared Tissue for Light-Sheet Microscopy
A glass capillary was glued with super-glue to the caudal side of the coronal section at a brain
region distant from the region of interest (i.e., orofacial primary motor cortex) and not within the
centres of light emission planes and objective (Fig. 12). The tip of the capillary was then mounted
to the microscope holder and the brain section was suspended from above into 63% TDE-filled
chamber. This chamber provided the brain section with a stable temperature environment
throughout the imaging process which took about 1/2 hour. For imaging the region of interest in
layer I, the orofacial primary motor cortex was imaged while the coronal slide was submerged
into the mounting solution facing its rostral aspect to the objective. Care was taken not to form air
bubbles in the chamber to avoid light scattering.
2.4.6.2 The Region of Interest
Based on previously published electrophysiology studies (Avivi-Arber et al., 2011b, 2017;
Awamleh et al., 2015) and Swanson anatomical atlas (Swanson, 2004) (Figs. 2, 11), the region of
interest included the superficial layer I at ~ 4 mm from the midline of the whole coronal section
(depicted with a red line) .
39
Figure 11. The region of interest (small yellow square) selected for scanning with the light-sheet 20X CLARITY objective spanned from the cortical surface at ~4 mm lateral to midline (red line) and included a total area of 438.9 μm x 438.9 μm x 1 mm.
2.4.6.3 Image Acquisition
A Zeiss light-sheet Z1 microscope was used for image acquisition with the following
specifications (Fig. 12):
Detection Optics: 20x/1.0 (CLARITY, RI=1.45)
Illumination Optics: 10x/0.2 x 2, 5x/0.1 x 2
Lasers: 405 nm (20mW), 488 nm (50 mW), 561 nm (20 mW), 638 nm (75 mW)
Camera: pCO Edge 5.5 x 2
Max Sample Dimensions: 10 x 10 x 20 (mm)
Field of View (20x): 439 x 439 (μm)
Software: Zeiss Zen Light-sheet 2014
Environmental Control: Zeiss (temperature/CO2)
40
Figure 12. A. A glass capillary is attached to the caudal aspect of the 2 mm-thick brain section. Red arrow is pointing at the area were the ROI is located. B. The glass capillary with the brain section are attached to the Zeiss light-sheet Z1 microscope and positioned in front of the camera (red arrow). C. Outside view of the Zeiss light-sheet Z1 microscope.
Images of the region of interest were acquired with a CLARITY objective (Clr Plan-Neofluor
20x/1.0, RI=1.45 (± 0,03), NA=1. Acquisition parameters were as follow:
Unilateral illumination: Since usually only the left- or right-side illumination provided a better
resolution image of the labelled neurones and astroglia, each plane was illuminated from either
the left or right light source and not both.
A separate track for each laser and camera color was used for each marker; GFAP (green 50),
NeuN (red 50) and DAPI (cyan).
Laser power range: 45- 90%
Exposure time: 29 – 129 ms
Computers used for image acquisition require very large storage space as well as large random-
access memory (RAM) for image processing. The storage space of each acquired image of 2 mm-
thick brain tissue was ~100 GB/scan. This storage volume was too large to be handled by the
computers available at our imaging facility. Therefore, we carried out 2 scans of the region of
interest which included 1 mm3 of the rostral aspect of the region of interest, and then 1 mm3 of
the caudal aspect of the region of interest. We here report data collected from the rostral aspect
only (i.e., ~60 GB/scan).
41
After imaging, the section was stored in PBST at room temperature protected from light.
2.4.7 Image Processing
Image analysis was carried out with Imaris Software 9.2.0 (Bitplane) for 3D reconstruction. The
Z- stacks acquired with the light-sheet microscope Z1 were converted from Zen (.czi) files to
Imaris (.ims) files using the Imaris File Converter x64 9.0.1 application. After background
subtraction and thresholding for the green channel that corresponds to GFAP positive cells
(GFAP+), a systematic region of interest delineating Layer I was cropped from the total volume
of the acquired image.
2.4.7.1 Identification of Layer I Cytoarchitectonic features were used to delineate the border between cortical layer I and layers
II/III. Layers II/III, as compared with layer I, were characterised with a significantly larger number
of NeuN positive (NeuN+) nuclei but only sparse GFAP immunoreactivity. In contrast, layer I
was characterised by a rich network of GFAP+ processes and sparse NeuN immunoreactivity.
The selected region of interest included layer I and excluded the glial limitans due to a
significantly higher GFAP immunoreactivity of the glial limitans that limited the software ability
to trace individual GFAP+ processes (Fig. 13).
2.4.8 Quantification of Morphological Parameters of Astroglial Processes Accurate morphological description of filamentous structures requires ultimate resolution to
capture the finest of structures of interest in our study, i.e., the astroglial processes. Therefore, the
Filament Tracer application of Bitplane Imaris, an advanced software for automatic detection of
filament-like structures, was used for morphometric analysis of astroglial processes in all spatial
directions (Fig. 13 B and C).
42
Figure 13. A. 3D image of 1 mm-thick cortical tissue showing the features used to select the region of interest within layer I: the pia mater, composed of NeuN+ flat-shape nuclei (red), the glia limitans identified as a continuous layer of high intensity GFAP+ astroglial cells, cortical layer I is characterised by a rich network of GFAP+ processes while layers II/III below show a significantly larger number of NeuN+ nuclei and sparse GFAP+ cells. B. Illustrates the region of interest within layer I selected for subsequent morphometric analysis of GFAP+ processes. Bottom yellow line marks the approximate border between layer I and layers II/III. Top yellow line marks an approximate border between layer I and the glial limitans. C. Bitplane Imaris software masked the GFAP+ processes (white) within the region of interest for subsequent morphometric analysis.
The tracing was done by applying the threshold-based algorithm that is based on an absolute
intensity threshold of GFAP+ filamentous structures (processes). The analysis took approximately
8 hours per scan.
2.4.8.1 Morphological Parameters
Several statistic values were calculated automatically by the Imaris software and compiled in an
Excel Sheet. For the purpose of our study, values from seven parameters were collected. The term
‘Filament’ is given by the software to the filamentous structures (astroglial processes)
(http://www.bitplane.com/download/manuals/ReferenceManual6_1_0.pdf).
1. Filament Area: the sum of the generated surfaces of a frustum (truncated cone).
2. Filament Length (sum): the sum of the length of all filaments.
3. Filament mean diameter: the mean diameter within a filament. Each point of a filament
line has its individual measured diameter. The diameter is measured as the shortest
distance from the centre line to the surfaces defined by the lower threshold.
4. Filament volume: the sum of the volume of all edges (cones) which compose a filament
5. Filament straightness: h = the distance between two branch points. The filament
straightness is h per length of the filament.
43
6. Volume of the region of interest within layer I; use for subsequent normalization of the
length, surface area and volume of the astroglial processes.
Changes in the complexity of astroglial morphology were determined by calculating the
surface area/volume ratio from the data provided by the software.
2.5 Data Analysis and Sample Size Calculation The densely intermingled GFAP+ processes within layer I of the orofacial primary motor cortex
did not allow analysis of morphological features of GFAP+ processes per individual cell.
Therefore, data analysis was based on automatic software quantification of global morphological
features of GFAP+ processes within the region of interest.
Our published and recent studies indicate large effect size (21-25%) between groups in primary
outcomes. According to G*Power calculation, the minimum sample size required to obtain
statistically significant results for ANOVA test with 80% power and a= 0.05 is n = 7/group, and
for 4 groups a total of 28 rats. The outcome variables were transformed to obtain a normal
distribution. The independent variable was the study group, i.e., Endo, Exo, Sham or Naive. The
dependent variables were: sum of the total surface areas of all GFAP+ filaments, sum of the total
length of all GFAP+ filaments, filaments’ mean diameter, sum of the total volume of all GFAP+
filaments, and median filament straightness. The total volume (%), surface area, and length of
GFAP+ filaments were normalised by the region of interest. Sigma Plot 11 (Systat Software, San
Jose, CA, USA) was used to perform the statistical analysis. One-way ANOVA followed by the
post-hoc Duncan test determined whether the independent variable had an effect on any of the
independent variables. A p-value < 0.05 was considered a statistically significant difference. Data
are presented as means + SEM.
2.6 Excluded Data A total of 32 rats were initially included in the study however, data of 10 rats were excluded
because of animal death during the general anaesthesia (n=2), or inadequate perfusion (n=3)
(Table 4). Inadequate perfusion was associated with bright wide-diameter (> 6 µm) GFAP+
structures consistent with blood-filled blood vessels (Fig. 14 A,B) (Whittington and Wray, 2017).
44
Accordingly, for the mean diameter parameter, all the values larger than > 6 µm were not included
for data analysis.
Additional 5 animals from the Naïve (n=3) and Exo (n=2) groups were excluded from the study
due to inadequate quality of the images acquired with the light-sheet microscope. Three images
had bright/ dark stripe artifacts which are a common occurrence in light-sheet microscopy (Power
et al., 2017) (Fig. 14 C,D). One Naïve rat was excluded due to a persistent technical problem with
the statistical data extraction in the Imaris software. Thus, this study reports on a total of 22 rats
with some groups having 5 rats.
Figure 14. A. 3D image of 1 mm-thick brain tissue from a rat that underwent inadequate perfusion and subsequent immunolabelling with GFAP marker in green. White arrows show >6 µm-thick GFAP+ structures consistent with blood-filled blood vessels (scale 100 μm). B. Enlarged insert from figure A. C and D. 3D image of 1 mm-thick brain tissue which underwent immunolabelling with GFAP marker in green. Image shows bright and dark stripe artifacts which are a common occurrence in light-sheet microscopy (scale 100 μm). C. A lateral view. D. A superior view.
45
Table 4. Summary of study groups, number of animals included or excluded from the study and
the reason for exclusion.
Experimental Group
Number of Animals
Included for analysis
Number of Animals
Excluded Reasons for exclusion
Naïve 5 3
- Two animals with bright/dark
stripe artifacts - One animal with unsolved
technical problem in statistical data extraction by Imaris software
Sham 6 2
- One animal with inadequate
perfusion and bright blood-filled blood vessel artifacts
- One animal died during general anaesthesia
Endo 6 2
- Two animal with inadequate
perfusion and bright blood-filled blood vessel artifact
Exo 5 3
- Two animals with bright/dark
stripe artifacts - One animal died during general
anaesthesia
Total
22 10
46
Results
In the present study, we have utilised the CLARITY technique to render 2 mm-thick rat coronal
brain sections optically transparent. We then utilised immunofluorescence labelling with antibody
markers specific to astroglial filaments (GFAP) and neuronal nuclei (NeuN). We subsequently
applied light-sheet microscopy for 3D imaging of a motor cortex region we have previously
defined as the centre of the rat orofacial primary motor cortex. By subsequently employing the
Bitplane Imaris software for 3D reconstruction and morphometric analysis of the GFAP- and
NeuN-labelled cells within the superficial layers I-III of the motor cortex we have identified their
laminar distribution and have also characterised morphological features of astroglial processes
within layer I of naïve rats and rats receiving tooth extraction, endodontic treatment or sham
operation.
3.1 3D Characterisation of Astroglial and Neuronal Cytoarchitecture and Morphology within the Superficial Layers of the Rat Orofacial Primary Motor Cortex
We have identified a laminar cytoarchitecture of the primary motor cortex demonstrated by NeuN-
and GFAP-immunoreactivity (i.e., NeuN+ and GFAP+, respectively). Fig. 15 C shows a 3D
image of a 438.9 µm x 438.9 µm x 1 mm brain tissue from a representative rat immunolabelled
with the NeuN and GFAP markers. The most superficial layer comprised a thin layer of NeuN+
flat-shape nuclei corresponding to the pia mater, i.e., the innermost layer of the meninges. The pia
closely apposed a continuous layer of high-intensity GFAP+ cell bodies and processes, which are
known as the glia limitans superficialis (glial limiting membrane) (also see Fig. 16). This
membrane also surrounds the perivascular space surrounding the cortical parenchymal blood
vessels and is referred to as the glia limitans perivascularis (Fig. 17). Immediately below the glia
limitans is cortical layer I, which comprised a dense network of GFAP + cell bodies and processes,
some of which project to the glia limitans. The immediately adjacent inner cortical layers,
corresponding to cortical layers II/III, comprised an abundant number of NeuN+ round-shaped
nuclei, significantly larger than the number of NeuN+ cells in layer I. In contrast, GFAP+ cells
appear to be significantly more abundant in layer I than in layers II/III. DAPI was able to label (in
blue) nuclei within the cortex and nuclei of the Pia mater located above the glia limitans (Fig. 16
D and Fig. 18 A).
47
Figure 15. A. A 2D image of a Nissl-stained coronal section through the orofacial sensory-motor cortex of a Sprague Dawley rat at ~ 3 mm anterior to Bregma. Superimposed are the jaw (red) and tongue (blue) motor representation areas as we have previously mapped and documented. B. A schematic diagram obtained from Swanson’s Atlas of the Rat Brain). Reprinted with permission from John Wiley and Sons, Journal of Comparative Neurology, Brain maps 4.0 - Structure of the rat brain: An open access atlas with global nervous system nomenclature ontology and flatmaps, Swanson L, Copyright (2004) (Swanson, 2004), which corresponds to the histological section in A, indicating the different cortical layers numbered with Roman numerals from superficial to deep (I-VI). C. A 3D image of a 438.9 µm x 438.9 µm x 1 mm (scale 50 μm) brain tissue showing the superficial cortical layers I and II/III as well as the pia mater and glia limitans. White arrow pointing at the pia mater, composed of NeuN+ flat-shape nuclei (red). Juxtaposing below the pia is the glia limitans (white arrow), which comprises a continuous layer of high intensity GFAP+ astroglial cell bodies and processes. (GFAP+: immunoreactive glial fibrillary acidic protein; NeuN+: neuronal nuclei).
48
Figure 16. A. Superior view of glia limitans superficialis showing high-intensity GFAP+ cells (green) (soma and processes). Superior view of a blood vessel (white arrow) penetrating the cortex; and NeuN+ neuronal nuclei (red) (scale 50 μm) B. Lateral view of a blood vessel (white arrow) penetrating the cortical parenchyma surrounded by GFAP+ astroglial cells (green) forming the glia limitans perivascularis; NeuN+ neuronal nuclei are marked in red (scale 50 μm). C. Schematic representation of the superficial membranes of the cortex showing that the glia limitans (green) lies between the pia mater and the cerebral cortex. D. 40 µm thick image showing GFAP + cells (green) within the superficial layer of motor cortex forming glia limitans, DAPI (blue) labelling of any nucleus within the cortex and the pia mater above the glia limitans (scale 50 μm).
49
Figure 17. A. GFAP+ cells covering the cortical surface area form the glia limitans superficialis and GFAP+ cells surrounding blood vessels form the glia perivascularis. B. Enlarged insert from Figure A showing the glia limitans perivascularis (scale 50 μm).
50
Figure 18. A. A 3D image of a 1 mm-thick cortical tissue showing cells immunolabelled with GFAP (GFAP+, green), a specific marker of astroglial cytoskeleton, NeuN (NeuN+, red), a specific marker of neuronal nuclei, and DAPI (blue), a non-specific marker of cell nuclei. B. Same image as in A showing GFAP+ cells. C. Same image as in A showing NeuN+ cells (scale 100 μm).
51
3.2 Morphological Features of GFAP-Immunoreactive Processes: Effects of Maxillary Molar Tooth Extraction versus Endodontic Treatment
Tooth extraction (Exo group), had a significant effect on the diameter of astroglial processes
within the orofacial primary motor cortex. The mean diameter of astroglial processes of rats in
the Exo group was significantly smaller than that of rats in the Naïve and Sham groups (ANOVA
F3,21=4.10 p= 0.022; post hoc Duncan’s p=0.005, Sham: p= 0.028, respectively) and small, but
not statistically significant, than that of rats in the Endo group. In contrast, the mean diameter of
astroglial processes of rats of the Endo group was similar to that of rats in the Naïve and Sham
groups (post hoc Duncan’s p=0.148, 0.569, respectively), and was larger, but not statistically
significant than that of rats in the Exo group (post hoc Duncan’s p=0.066) (Fig. 19 A).
Tooth extraction, but not endodontic treatment, also had a significant effect on the straightness of
astroglial processes. In comparison to Naïve and Sham groups, in the Exo group the astroglial
processes were significantly straighter (ANOVA F3,21=3.77 p= 0.030; post hoc Duncan’s p=0.011,
0.032, respectively) (Fig. 19 B).
Figure 19. Mean diameter (A) and straightness (B) of astroglial processes. Diameter data is presented as group-means and SEM; Straightness data is presented as group-medians and SEM. Tooth extraction was associated with a significantly smaller diameter and straighter astroglial processes.
52
No significant differences were found across the study groups in the volume, surface area to
volume ratio, and length of astroglial processes (ANOVA, p > 0.050) (Fig. 20).
Figure 20. A. Percent volume of all GFAP-labelled cells. B. Ratio of surface area to volume of all GFAP-labelled cells. C. Total length of all GFAP-labelled processes. Data presented as group-means and SEM.
53
Discussion
This study has successfully applied, for the first time, the novel CLARITY (Clear Lipid-
exchanged Acrylamide-hybridised Rigid Imaging-compatible Tissue-hYdrogel) technique to
clear a 2 mm-thick section of the orofacial primary motor cortex of adult male Sprague-Dawley
rats. With subsequent immunohistochemistry of the optically cleared brain section and the aid of
light-sheet microscopy, we have successfully obtained, for the first time, large-volume high-
resolution 3D images of astroglia and neurones within the superficial layers (I-III) of a cortical
region we have previously identified as the centre of the orofacial primary motor cortex. This
study has also applied, for the first time, the Imaris software to automatically quantify
morphological features of astroglial processes and test the effects of endodontic treatment versus
tooth extraction on these morphological features. Our novel findings suggest that tooth extraction
has a statistically significant effect, one week later, on the morphological features of astroglial
cells within the superficial layers of the rat orofacial primary motor cortex. Our results indicate
that in comparison with Naïve rats and sham-operated rats, tooth extraction is associated with
thinner and straighter astroglial processes. On the other hand, endodontic treatment has no
statistically significant effect on the morphological features of astroglial cells. The mean diameter
and median straightness of astroglial processes within the primary orofacial motor cortex of rats
receiving endodontic treatment were similar to those in naïve rats and those in rats receiving sham
operation. As discussed below, the differential effects of tooth extraction versus endodontic
treatment on the morphological features of astroglia within the orofacial primary motor cortex
may reflect differences in the rat sensory-motor function and functional adaptation (or
maladaptation) to changes in orofacial sensory-motor functions induced by these treatments.
4.1 3D Visualisation of Astroglia with CLARITY Astroglia communicate with each other and with neurones through an extensive network of
processes that span within and through different regions and layers of the brain (Kettenmann et
al., 2008; Verkhratsky and Butt, 2013; Verkhratsky and Nedergaard, 2018). Exploring their
complex anatomy and connectivity requires 3D imaging of intact thick brain tissues. Conventional
immunohistochemistry relies on a selective selection of a certain number of thin sections
measured in a few μm and up to several tens of μm out of a whole brain specimen. This
unavoidably results in a loss of information and an inability to achieve 3D high-resolution images
54
of complex cytoarchitecture that spans a few millimeters or even centimeters within thick brain
tissues or even the whole brain. Moreover, conventional immunohistochemistry is an irreversible
process involving mounting of brain sections on slides. Thus, the slightest mistake in the process
can ruin the whole sample or even a whole experiment. It also does not allow for re-staining or
additional staining. The CLARITY technique, however, can overcome all these limitations of the
conventional technique. CLARITY is based on the creation of a hydrogel scaffolding that
stabilises the brain tissue and allows for membrane lipids to be removed without losing structural
details and antigenicity of the tissues therein. This results in an intact, optically-transparent brain
tissue that is permeable to large molecules and their chromophores including cellular antibodies
for immunofluorescence labelling. It also facilitates 3D imaging of cells within a whole brain or
thick tissue sections. In addition, there is no need for irreversible mounting, and the cleared tissue
samples can be stored for months and go through multiple rounds of immunostaining with
different fluorophores, which is particularly useful for multiplexing beyond the limits of spectral
separation (i.e., using various fluorophores that absorb and emit light in different parts of the
visible spectrum in order to detect multiple molecules in a tissue) (Miller et al., 2016; Tomer et
al., 2014). In the present study we used and optimised immunostaining with Anti-GFAP, which
is a standard and specific marker of astroglial filaments (Bastrup and Larsen, 2017; Bignami and
Dahl, 1977; Chung and Deisseroth, 2013; Costantini et al., 2015; Eng et al., 2000; Garcia-Cabezas
et al., 2016; Tomer et al., 2014) We also used Anti-NeuN, which is a standard and specific marker
of neuronal nuclei (Gusel'nikova and Korzhevskiy, 2015; Kim et al., 2009; Mullen et al., 1992),
and DAPI, which is a blue-fluorescent stain of nuclear DNA in any cell. Thus, the present study
has successfully applied for the first time the CLARITY technique to optically clear a 2 mm-thick
sections of the orofacial primary motor cortex and has successfully optimised immunostaining of
astroglial cells as well as neurones and cell nuclei.
The novel light-sheet microscope allows for high-speed and high-resolution 3D imaging of a few
millimeters- to a few centimeters-thick intact cleared tissues. Thus, the light-sheet microscopy
can exploit the CLARITY potential for 3D imaging of large populations of cells with complex
cytoarchitecture spanning millimetres or even centimeters within an intact brain tissue (Dodt et
al., 2007; Silvestri et al., 2015; Stefaniuk et al., 2016; Tomer et al., 2014). However, these images
generate an enormous amount of data that cannot be quantified manually. The Bitplane Imaris
software can overcome this problem by allowing automatic identification and quantification of
some morphological features of cells in the brain. Noteworthy is that the present study is the first
55
to utilise the Imaris software for automatic identification and quantification of morphological
features of astroglial processes with the superficial layer I of a 2 mm thick section of the orofacial
motor cortex.
4.2 3D Characterisation of Astroglial and Neuronal Cytoarchitecture and Morphology within the Superficial Layers of the Rat Orofacial Primary Motor Cortex
Our study is the first one showing large-volume (~0.5 x 0.5 x 1 mm3) high-resolution 3D images
of the highly organised laminar cytoarchitecture of the superficial layers of the orofacial primary
motor cortex. Our findings are consistent with the findings of published studies that have utilised
conventional immunohistochemistry and histology. Of particular note is the abundance of
neuronal nuclei within layers II/III and their sparse distribution in layer I. In contrast, the highly
organised astroglial cells are dispersed in layers II/III but abundant in layer I and form a dense
network of processes, some of which project to the most superficial layer of the cortex known as
the glia limitans superficialis (glial limiting membrane). Indeed, other studies have shown that in
cortical layers II and III, the mean astroglia-to-neuron ratio is approximately 1∶5 (Fleischhauer
and Vossel, 1979; Kalman and Hajos, 1989; Takata and Hirase, 2008) and there is 1.6 times higher
density of astroglial cells in layer I than in layers II and III (Takata and Hirase, 2008).
The finding of NeuN+ flat cells in the pia mater corresponds with previously published studies
showing that the meninges, including the pia mater, harbour neuronal precursor cells (Bifari et
al., 2015; Nakagomi and Matsuyama, 2017). Moreover, the pia mater is a highly vascularized
layer (Adeeb et al., 2013) and therefore, the presence of NeuN+ cells in the pia mater might
correspond to the vascular innervation of blood vessels (Pigolkin Yu et al., 1985). Interestingly,
nowadays, it is accepted that the only intracranial structure associated with pain perception (e.g.,
headache) is the dura mater that is innervated by neurones exhibiting properties characteristic to
nociceptors found in other body tissues (Messlinger et al., 2008; Strassman and Levy, 2006).
Nevertheless, recent observations during intracranial brain surgeries in awake humans suggest
that in fact cerebral vessels and the pia mater are sensitive to mechanical stimuli that can induce
acute pain perception in orofacial regions innervated by the trigeminal nerve (Fontaine et al.,
2017, 2018).
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The glia limitans superficialis is a continuous layer composed of astroglial soma and a dense
meshwork of astroglia processes that are firmly attached to an outer basal lamina that makes
intimate contact with cells of the pia mater (Karasek et al., 2004; Liu et al. 2013). Astroglial
processes tightly ensheath the blood vessels that penetrate into the cortical parenchyma. This
nearly-complete coverage of blood vessels through abundant astroglial endfeets is known as the
‘glia limitans perivascularis’. The glia limitans superficialis is continuous with the glia limitans
perivascularis and together they play a role in the control of the blood-brain barrier (Quintana,
2017). In addition, the perivascular endfeet can release vasoactive substances that can mediate
cerebral ‘functional hyperemia’, i.e., the increased or decreased cerebral blood flow associated
with increased or decreased neuronal activity (Dunn and Nelson, 2014; MacVicar and Newman,
2015).
The finding of a rich network of astroglial cells within the superficial layers of the orofacial
primary motor cortex supports previously published data (Awamleh et al., 2015) suggesting that
superficial astroglial cells are involved in modulating motor cortex functional neuroplasticity (i.e.,
decreased excitability) induced by acute noxious stimulation of the dental pulp. This study has
shown that the application of an astroglial inhibitor to the surface of the orofacial primary motor
cortex can reverse the neuroplasticity induced by the noxious stimulation (Awamleh et al.,
2015). While in this study the exact cortical site of action of the astroglial inhibitor is unclear, it
likely diffused into the cortex to exerted its effects, at least in part, on the astroglial cells within
the superficial cortical layers.
While the present study utilised the CLARITY immunohistochemistry in 2 mm-thick brain tissue
to explore morphological features of marginal astroglial cells within layer I of the orofacial
primary motor cortex, most of the available studies exploring astroglial structure and morphology
have used mice and not rats as well as monkeys and human, and have characterised protoplasmic
astroglia within layer II – VI of different cerebral cortical regions (Miller et al., 2016; Oberheim
et al., 2008, 2009; Rodriguez et al., 2009; Sun and Jakobs, 2010; Wilhelmsson et al., 2004). In
addition, the majority of these studies have utilised the conventional immunohistochemistry
technique using small (mm) and thin (40µm) brain sections which contain only a few astroglial
cells and utilised immunolabelling with different markers of astroglial cells (e.g., S-100, Glt,
ALDA1L, GFAP), high-magnification (60x) imaging techniques and subsequent manual
quantification of morphological features such as total diameter of the labeled astroglia, number of
57
processes, the length of the processes, and the diameter of the soma or the thickest astroglial
process. Therefore, we could not have made any comparison with published data. We have found
that the mean diameter of astroglial processes within layer I ranged from 0.46 – 4.00 µm and the
Mean + SEM was 1.71 + 0.15 µm. Oberheim et al. found in mice that the diameter of the thickest
process measured 2.6 µm + 0.2 µm (Oberheim et al., 2009).
In a recently published study, Miller and Rothstein (Miller et al., 2016) have utilised the
CLARITY technique in transgenic mice expressing the astroglial proteins glutamate transporter
(Glt1) and tdTomato-astros, and further immunolabelled with GFAP. By using single- and multi-
photon microscopy to image 0.5- to 1.0 mm-thick brain tissue, they have characterised the laminar
distribution of the different astroglial markers. However, they have not provided any details
related to the cytoarchitecture and morphological features of the rich network of GFAP+ astroglial
processes within the cortical layer I.
4.3 Morphological Features of GFAP-Immunoreactive Processes: Effects of Maxillary Molar Tooth Extraction versus Endodontic Treatment
Tooth extraction, but not endodontic treatment, had a statistically significant effect on the
morphological features of astroglial cells within the orofacial primary motor cortex. In
comparison with naïve and sham-operated rats, in rats receiving tooth extraction, the astroglial
processes were significantly thinner (smaller mean diameter) and straighter, and they were also
thinner but not statistically significant than those in rats receiving endodontic treatment. There
were no statistically significant differences between rats receiving endodontic treatment and those
receiving sham operation or no treatment (i.e., the Naïve group).
The differences in the effects on cortical astroglial between tooth extraction and endodontic
treatment may be related to differences in the extent of tissue injury, sensory denervation and the
altered motor function. Following tooth extraction, there is major damage to hard and soft tissues
as well as a complete loss of sensory inputs due to the lack of occlusal contacts and the loss of
periodontal as well as pulpal tissues. In contrast, following endodontic treatment, the amount of
tissue injury is significantly smaller, and there is also only a partial loss of occlusal contacts with
no loss of periodontal ligament. Therefore, it is possible that the changes induced by the
58
endodontic treatment were not significant enough to result in structural and morphological
changes in astroglial processes, which is consistent with the notion that motor cortex plasticity
emerges in response to significant changes in external factors or experiences including changes
in orofacial sensory-motor functions. However, these differences may also provide evidence that
the orofacial primary motor cortex has the capability to adapt and be modelled in a task-dependent
manner, but they may also suggest the existence of different underlying mechanisms (Ebner,
2005; Haydon et al., 2014; Monfils, 2005; Remple et al., 2001). It is also possible that the changes
induced by endodontic treatment were too small to be detected by our methods. It is important to
consider that the analysed data was underpowered and a large effect (21-25%) was contemplated
for this study (see below study limitations). Another possibility relates to the reliability of our
combined methods (Light-sheet microscope 20x objective and Imaris software) to accurately
image astroglial processes and identify and delineate their boundaries for subsequent analysis of
morphological features.
Similar study limitations to those described above may also account for our findings that neither
tooth extraction nor endodontic treatment had any significant effect on any of the other measured
variables, including volume (%), surface area (normalised), surface area to volume ratio and sum
length of astroglial processes.
Our findings of decreased dimensions of astroglial processes are consistent with a couple of
previously published studies. In a structural magnetic resonance study in rodents, molar tooth
extraction was associated with a significantly decreased volume of the orofacial primary motor
cortex region as well as other cortical regions involved in processing sensory and motor functions
(Avivi-Arber et al., 2017). Our findings are also consistent with electrophysiological studies
showing that molar tooth extraction is associated with decreased jaw and tongue motor
representations in the orofacial primary motor cortex (Avivi-Arber et al., 2015b).
To our best knowledge, no other study has utilised the CLARITY immunohistochemistry to test
the effects of intraoral injury on the morphological features of astroglia within the most superficial
layer I of the orofacial primary motor cortex. Nevertheless, the findings of the present study
appear to be in contradiction to the study by Laskawi et al., who have used conventional
immunohistochemistry in rats who underwent transection of the facial motor nerve that supplies
motor innervation to the facial muscles and vibrissae. The facial nerve transection was associated with
59
increased immunoreactivity of various astroglial antigens in layers I/II and III/V of the primary motor
cortex including S-100 protein which is a Ca2+-binding protein located mainly in the astroglial
cytosol, GFAP which is a cytoskeletal filament protein, as well as connexin 43 which is a gap junction
protein. The increased immunoreactivity occurred within 1 hour following the nerve transection and
lasted for 2 to 5 days (Laskawi et al., 1997). The difference between their findings and ours may be
due to the amount of peripheral injury, type of injured neural structure (motor vs sensory) or the
postoperative time when these changes were sampled.
The findings of the present study of thinner and straighter astroglial cells post-extraction also
contradict the notion that peripheral (e.g., nerve injury) and central (e.g., brain injury) injuries or
neurological diseases (e.g., stroke), always induce astroglial reactivity that manifests in
hypertrophy (i.e., reactive astroglia) within cortical (e.g., sensory and motor cortex) and
subcortical (e.g., brainstem) brain regions. These hypertrophic changes result in upregulation of
GFAP expression, increased volumes of soma and processes and increased immunoreactivity of
astroglial antigens including GFAP. Nevertheless, such changes depend on many factors
including the type of injury and its severity, and brain region (Bernardinelli et al., 2014; Cheung
et al., 2015; Childers et al., 2014; Genoud et al., 2006; Liddelow and Barres, 2015; Miller et al.,
2016; Oliet et al., 2001; Perez-Alvarez et al., 2014; Sun and Jakobs, 2012).
The contradicting findings reported in the present study as compared with those reported by other
studies may be related to different study designs such as animal species, type and location of the
injury, as well as the follow-up time since it has been documented that different brain mechanisms
are involved at different points of time. It may also be related to the types of
immunohistochemistry, imaging and data analysis techniques that were applied in the different
studies.
4.3.1 Clinical Implications It is now clear that astroglia not only provide metabolic support to neurones, but they also play an
integral and essential role in maintaining and participating in neuronal synaptic activity. Astroglia
release and remove neurotransmitters to and from the synaptic cleft, they can also provide
neuronal support and impact synapse formation and synaptic pruning and help maintain blood
flow and blood-brain barrier (Liddelow and Barres, 2015). Significant to the present study,
60
peripheral (e.g., nerve injury) and central (e.g., brain injury) injuries as well as neurological
diseases (e.g., stroke), have been associated with astroglial plasticity manifested as changes in the
structure and function of astroglial cells. Such changes can have a rapid or slow onset and last for
a short duration and/or chronically and may subsequently enhance or impede recovery of sensory-
motor functions following injury or disease (Bernardinelli et al., 2014; Cheung et al., 2015; Chung
and Deisseroth, 2013; Genoud et al., 2006; Liddelow and Barres, 2017; Miller et al., 2016; Oliet
et al., 2001; Perez-Alvarez et al., 2014). However, little is known of the involvement, role and
underlying mechanisms of motor cortex astroglia in mediating neuronal response and sensory-
motor behaviour to peripheral injury including following intraoral injury such as tooth extraction
and/or pulpectomy. Nevertheless, this information is of clinical significance since patients
receiving endodontic treatment or tooth extraction develop postoperative sensory-motor
impairments such as pain and limited or altered jaw movement and altered biting forces (for
reviews see Avivi-Arber et al., 2011d, 2018; Sessle et al., 2013a; Trulsson et al., 2012a).
Moreover, in a significant number of patients these acute impairments may develop into chronic
sensory-motor conditions such as chronic orofacial pain, phantom bite or occlusal dysaesthesia
(Hara et al., 2012; Kelleher et al., 2017; Marbach and Raphael, 2000; Melis and Zawawi, 2015;
Nixdorf et al., 2012; Polycarpou et al., 2005). For example, in 5-12% of the patients undergoing
endodontic treatment and in 3% of the patients receiving tooth extraction, acute pain develops
into a chronic pain condition (Nixdorf et al., 2010b,c; Polycarpou et al., 2005). Thus, a better
understanding of the mechanisms underlying the development, maintenance and resolution of
these conditions is crucial for the development of improved therapeutic strategies that target, for
example, astroglial processes.
4.4 Study Limitations and Future Directions The present study has successfully utilised the CLARITY immunohistochemistry technique in 1-
2 mm-thick brain tissue to characterise cytoarchitecture features of astroglia and neurons within
the superficial layers of the orofacial primary motor cortex as well morphological features of
astroglial processes, and to quantify the effects of tooth extraction versus endodontic treatment on
these features.
The CLARITY immunohistochemistry is a multi-step technique that requires significant
optimisation and thus a large number of factors may affect the accuracy of the outcome. These
61
include quality of the fluorescence images that can be affected by the adequacy of the animal
perfusion, degassing the hydrogel solution to generate as little as possible air bubbles within the
tissue, volumetric changes in the tissue after clearing, the quality and concentration of the
antibodies and their ability to penetrate the full thickness of the brain section to achieve a high
signal-to-background noise ratio and minimise nonspecific antibody binding. In the present study,
although we have strictly adhered to the protocol for all brain samples, technical problems have
precluded the inclusion of all animal samples in the final data analysis, which may have affected
the statistical power.
In general, statistical power is affected by effect size of the intervention and the size of
the sample used to detect effect of treatment. In the present study, a large effect size (21-25%)
was estimated based on our previously published studies, and it is possible that the effect of
endodontic treatment was smaller than the proposed effect size. Due to the exclusion of some rats
from all four groups and the reduction of the sample size to 6 or even 5 animals per group, it is
possible that the study did not have enough power to detect small changes induced by endodontic
treatment.
Another limitation of the study is the use of only one marker of astroglial cells. It is known that
antibodies against GFAP label only the main processes of astroglial cells that contain intermediate
filaments, and it does not label the fine distal processes. It has been suggested that GFAP
delineates only approximately 15% to 20% of the total volume of astroglial cells in the cortex
(Sun and Jakobs, 2012; Verkhratsky and Butt, 2013). Therefore, the use of only one marker of
astroglia may have underestimated the effect of treatments on finer branches of the studied
astroglia, as well as the 3D features quantified in this study. Nevertheless, GFAP is a specific and
well-documented marker of astroglial cells that is conventionally used for immunohistochemical
identification of astroglial cells and for characterisation of morphological changes occurring
following peripheral or central injuries (McKeon et al., 2018; Sofroniew et al., 2010).
Another important limitation to consider is that when excited, red blood cells emit fluorescence
within a wide range of wavelengths including the wavelength of the chromophore used in the
present study to stain GFAP+ cells (488 nm). Therefore, it is difficult to distinguish between fine
blood vessels and astroglial cells (Whittington and Wray, 2017).
62
A common drawback and limitation of the light-sheet microscopy is the appearance of dark and
bright artifactual stripes in the 3D images. These artifacts result from the unilateral illumination
of the brain sections and the existence of optical obstacles (e.g., bubbles) that obscure the light-
sheet and result in light scattering and/or absorption. Since such artifacts could have affected the
accuracy of the morphometric analysis, brains with such artifacts were excluded from the present
study (see Chapter 2).
The use of only male rats precluded any assessment of possible sex differences. Sex differences
were previously documented in rats and humans in the effects of orofacial injury on sensory and
motor functions (Cairns et al., 2001, 2002, 2003; Komiyama et al., 2005). Future studies could
make use of both male and female rats to investigate possible sex differences in the effects of
endodontic treatment and tooth extraction on the morphological features of astroglial cells within
the orofacial primary motor cortex.
Future studies with a larger number of animals that can investigate possible structural changes
following intraoral treatment at different postoperative time points and different cortical and
subcortical brain regions. Thereby add further insights into the differential spatial-temporal
regulation of GFAP after endodontic treatment and tooth extraction.
Enabling scientists to obtain high-resolution volumetric images of thick cleared tissue and the
ability to quantify morphometric features of astroglial cell will likely yield groundbreaking
findings that would improve our understanding of astroglial plasticity in health and disease.
63
Conclusions
Considering the crucial role that astroglia play in supporting and modulating neuronal activity in
health and disease, and since injury and disease can induce rapid and chronic changes in astroglial
structure and function which can either facilitate or impede sensory-motor recovery, developing
novel methods to study astroglial structure is of paramount importance in neurophysiology
research. Thus, our modified and optimised CLARITY immunohistochemistry technique along
with our automatic Imaris software analysis protocol provide a novel tool to characterise astroglial
morphology and plasticity in health and following injury or in disease.
Our novel findings of the laminar organisation of astroglia and neurones within the orofacial
primary motor cortex and that tooth extraction, but not endodontic treatment, produces significant
changes in morphological features of astroglial processes, will facilitate pursuing future research
directions to address the role of astroglia within the orofacial primary motor cortex in normal and
pathological conditions. They also suggest that astroglial cells are a new and promising target for
improved therapeutic interventions and prevention of impaired sensory-motor functions induced
by injury or disease.
64
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